Chapter 14. Storage Engines and Table Types

Table of Contents

14.1. Overview of MySQL Storage Engine Architecture
14.1.1. The Common Database Server Layer
14.1.2. Pluggable Storage Engine Architecture
14.2. Supported Storage Engines
14.2.1. Choosing a Storage Engine
14.2.2. Comparing Transaction and Non-Transaction Engines
14.2.3. Other Storage Engines
14.3. Setting the Storage Engine
14.4. The MyISAM Storage Engine
14.4.1. MyISAM Startup Options
14.4.2. Space Needed for Keys
14.4.3. MyISAM Table Storage Formats
14.4.4. MyISAM Table Problems
14.5. The InnoDB Storage Engine
14.5.1. InnoDB Overview
14.5.2. InnoDB Contact Information
14.5.3. InnoDB Configuration
14.5.4. InnoDB Startup Options and System Variables
14.5.5. Creating the InnoDB Tablespace
14.5.6. Creating and Using InnoDB Tables
14.5.7. Adding and Removing InnoDB Data and Log Files
14.5.8. Backing Up and Recovering an InnoDB Database
14.5.9. Moving an InnoDB Database to Another Machine
14.5.10. InnoDB Transaction Model and Locking
14.5.11. InnoDB Performance Tuning Tips
14.5.12. Implementation of Multi-Versioning
14.5.13. InnoDB Table and Index Structures
14.5.14. InnoDB File Space Management and Disk I/O
14.5.15. InnoDB Error Handling
14.5.16. Restrictions on InnoDB Tables
14.5.17. InnoDB Troubleshooting
14.6. The MERGE Storage Engine
14.6.1. MERGE Table Problems
14.7. The MEMORY (HEAP) Storage Engine
14.8. The EXAMPLE Storage Engine
14.9. The FEDERATED Storage Engine
14.9.1. Description of the FEDERATED Storage Engine
14.9.2. How to use FEDERATED Tables
14.9.3. Limitations of the FEDERATED Storage Engine
14.10. The ARCHIVE Storage Engine
14.11. The CSV Storage Engine
14.11.1. Repairing and Checking CSV Tables
14.11.2. CSV Limitations
14.12. The BLACKHOLE Storage Engine

MySQL supports several storage engines that act as handlers for different table types. MySQL storage engines include both those that handle transaction-safe tables and those that handle non-transaction-safe tables:

With MySQL 5.1, MySQL AB has introduced a new pluggable storage engine architecture that allows storage engines to be loaded into and unloaded from a running MySQL server.

This chapter describes each of the MySQL storage engines except for NDB Cluster, which is covered in Chapter 15, MySQL Cluster. It also contains a description of the pluggable storage engine architecture (see Section 14.1, “Overview of MySQL Storage Engine Architecture”).

For answers to some commonly asked questions about MySQL storage engines, see Section A.2, “MySQL 5.1 FAQ — Storage Engines”.

14.1. Overview of MySQL Storage Engine Architecture

The MySQL pluggable storage engine architecture allows a database professional to select a specialized storage engine for a particular application need while being completely shielded from the need to manage any specific application coding requirements. The MySQL server architecture isolates the application programmer and DBA from all of the low-level implementation details at the storage level, providing a consistent and easy application model and API. Thus, although there are different capabilities across different storage engines, the application is shielded from these differences.

The MySQL pluggable storage engine architecture is shown in Figure 14.1, “The MySQL architecture using pluggable storage engines”.

Figure 14.1. The MySQL architecture using pluggable storage engines

The MySQL pluggable storage engine
          architecture

The pluggable storage engine architecture provides a standard set of management and support services that are common among all underlying storage engines. The storage engines themselves are the components of the database server that actually perform actions on the underlying data that is maintained at the physical server level.

This efficient and modular architecture provides huge benefits for those wishing to specifically target a particular application need — such as data warehousing, transaction processing, or high availability situations — while enjoying the advantage of utilizing a set of interfaces and services that are independent of any one storage engine.

The application programmer and DBA interact with the MySQL database through Connector APIs and service layers that are above the storage engines. If application changes bring about requirements that demand the underlying storage engine change, or that one or more additional storage engines be added to support new needs, no significant coding or process changes are required to make things work. The MySQL server architecture shields the application from the underlying complexity of the storage engine by presenting a consistent and easy-to-use API that applies across storage engines.

14.1.1. The Common Database Server Layer

A MySQL pluggable storage engine is the component in the MySQL database server that is responsible for performing the actual data I/O operations for a database as well as enabling and enforcing certain feature sets that target a specific application need. A major benefit of using specific storage engines is that you are only delivered the features needed for a particular application, and therefore you have less system overhead in the database, with the end result being more efficient and higher database performance. This is one of the reasons that MySQL has always been known to have such high performance, matching or beating proprietary monolithic databases in industry standard benchmarks.

From a technical perspective, what are some of the unique supporting infrastructure components that are in a storage engine? Some of the key feature differentiations include:

  • Concurrency — some applications have more granular lock requirements (such as row-level locks) than others. Choosing the right locking strategy can reduce overhead and therefore improve overall performance. This area also includes support for capabilities such as multi-version concurrency control or “snapshot” read.

  • Transaction Support — Not every application needs transactions, but for those that do, there are very well defined requirements such as ACID compliance and more.

  • Referential Integrity — The need to have the server enforce relational database referential integrity through DDL defined foreign keys.

  • Physical Storage — This involves everything from the overall page size for tables and indexes as well as the format used for storing data to physical disk.

  • Index Support — Different application scenarios tend to benefit from different index strategies. Each storage engine generally has its own indexing methods, although some (such as B-tree indexes) are common to nearly all engines.

  • Memory Caches — Different applications respond better to some memory caching strategies than others, so although some memory caches are common to all storage engines (such as those used for user connections or MySQL's high-speed Query Cache), others are uniquely defined only when a particular storage engine is put in play.

  • Performance Aids — This includes multiple I/O threads for parallel operations, thread concurrency, database checkpointing, bulk insert handling, and more.

  • Miscellaneous Target Features — This may include support for geospatial operations, security restrictions for certain data manipulation operations, and other similar features.

Each set of the pluggable storage engine infrastructure components are designed to offer a selective set of benefits for a particular application. Conversely, avoiding a set of component features helps reduce unnecessary overhead. It stands to reason that understanding a particular application's set of requirements and selecting the proper MySQL storage engine can have a dramatic impact on overall system efficiency and performance.

14.1.2. Pluggable Storage Engine Architecture

With MySQL 5.1, MySQL AB has introduced a new pluggable storage engine architecture that allows storage engines to be loaded into and unloaded from a running MySQL server.

14.1.2.1. Plugging in a Storage Engine

Before a storage engine can be used, the storage engine plugin shared library must be loaded into MySQL using the INSTALL PLUGIN statement. For example, if the EXAMPLE engine plugin is named ha_example and the shared library is named ha_example.so, you load it with the following statement:

INSTALL PLUGIN ha_example SONAME 'ha_example.so';

The shared library must be located in the MySQL server plugin directory, the location of which is given by the plugin_dir system variable.

14.1.2.2. Unplugging a Storage Engine

To unplug a storage engine, use the UNINSTALL PLUGIN statement:

UNINSTALL PLUGIN ha_example;

If you unplug a storage engine that is needed by existing tables, those tables become inaccessible, but will still be present on disk (where applicable). Ensure that there are no tables using a storage engine before you unplug the storage engine.

14.1.2.3. Security Implications of Pluggable Storage

To install a pluggable storage engine, the plugin file must be located in the MySQL plugin directory, and the user issuing the INSTALL PLUGIN statement must have INSERT privileges for the mysql.plugin table.

14.2. Supported Storage Engines

MySQL 5.1 supports the following storage engines:

  • MyISAM — The default MySQL storage engine and the one that is used the most in Web, data warehousing, and other application environments. MyISAM is supported in all MySQL configurations, and is the default storage engine unless you have configured MySQL to use a different one by default.

  • InnoDB — Used for transaction processing applications, and sports a number of features including ACID transaction support and foreign keys. InnoDB is included by default in all MySQL 5.1 binary distributions. In source distributions, you can enable or disable either engine by configuring MySQL as you like.

  • Memory — Stores all data in RAM for extremely fast access in environments that require quick lookups of reference and other like data. This engine was formerly known as the HEAP engine.

  • Merge — Allows a MySQL DBA or developer to logically group a series of identical MyISAM tables and reference them as one object. Good for VLDB environments such as data warehousing.

  • Archive — Provides the perfect solution for storing and retrieving large amounts of seldom-referenced historical, archived, or security audit information.

  • Federated — Offers the ability to link separate MySQL servers to create one logical database from many physical servers. Very good for distributed or data mart environments.

  • NDB — The Clustered database engine that is particularly suited for applications with high performance lookup needs that also require the highest possible degree of uptime and availability.

  • CSV — The CSV storage engine stores data in text files using comma-separated values format. You can use the CSV engine to easily exchange data between other software and applications that can import and export in CSV format.

  • Blackhole — The Blackhole storage engine accepts but does not store data and retrievals always return an empty set. The functionality can be used in distributed database design where data is automatically replicated, but not stored locally.

  • Example — The Example storage engine is “stub” engine that does nothing. You can create tables with this engine, but no data can be stored in them or retrieved from them. The purpose of this engine is to serve as an example in the MySQL source code that illustrates how to begin writing new storage engines. As such, it is primarily of interest to developers.

This chapter describes each of the MySQL storage engines except for NDB Cluster, which is covered in Chapter 15, MySQL Cluster.

It is important to remember that you are not restricted to using the same storage engine for an entire server or schema: you can use a different storage engine for each table in your schema.

14.2.1. Choosing a Storage Engine

The various storage engines provided with MySQL are designed with different use-cases in mind. To use the pluggable storage architecture effectively, it is good to have an idea of the benefits and drawbacks of the various storage engines. The following table provides an overview of some storage engines provided with MySQL:

FeatureMyISAMMemoryInnoDBArchiveNDB
Storage limits256TBYes64TBNo384EB[4]
TransactionsNoNoYesNoYes
Locking granularityTableTableRowRowRow
MVCC (snapshot read)NoNoYesYesNo
Geospatial supportYesNoYes[1]Yes[1]Yes[1]
B-tree indexesYesYesYesNoYes
Hash indexesNoYesNoNoYes
Full-text search indexesYesNoNoNoNo
Clustered indexesNoNoYesNoNo
Data cachesNoN/AYesNoYes
Index cachesYesN/AYesNoYes
Compressed dataYesNoNoYesNo
Encrypted data[2]YesYesYesYesYes
Cluster database supportNoNoNoNoYes
Replication support[3]YesYesYesYesYes
Foreign key supportNoNoYesNoNo
Backup / point-in-time recovery[3]YesYesYesYesYes
Query cache supportYesYesYesYesYes
Update statistics for data dictionaryYesYesYesYesYes
  • [1] Storage engine supports spatial data types but no indexing of such data

  • [2] Implemented in the server (via encryption functions), rather than in the storage engine

  • [3] Implemented in the server, rather than in the storage engine

  • [4] EB = exabyte (1024 * 1024 terabyte)

14.2.2. Comparing Transaction and Non-Transaction Engines

Transaction-safe tables (TSTs) have several advantages over non-transaction-safe tables (NTSTs):

  • They are safer. Even if MySQL crashes or you get hardware problems, you can get your data back, either by automatic recovery or from a backup plus the transaction log.

  • You can combine many statements and accept them all at the same time with the COMMIT statement (if autocommit is disabled).

  • You can execute ROLLBACK to ignore your changes (if autocommit is disabled).

  • If an update fails, all of your changes are reverted. (With non-transaction-safe tables, all changes that have taken place are permanent.)

  • Transaction-safe storage engines can provide better concurrency for tables that get many updates concurrently with reads.

You can combine transaction-safe and non-transaction-safe tables in the same statements to get the best of both worlds. However, although MySQL supports several transaction-safe storage engines, for best results, you should not mix different storage engines within a transaction with autocommit disabled. For example, if you do this, changes to non-transaction-safe tables still are committed immediately and cannot be rolled back. For information about this and other problems that can occur in transactions that use mixed storage engines, see Section 13.4.1, “START TRANSACTION, COMMIT, and ROLLBACK Syntax”.

Non-transaction-safe tables have several advantages of their own, all of which occur because there is no transaction overhead:

  • Much faster

  • Lower disk space requirements

  • Less memory required to perform updates

14.2.3. Other Storage Engines

Other storage engines may be available from third parties and community members that have used the Custom Storage Engine interface.

You can find more information on the list of third party storage engines on the MySQL Forge Storage Engines page.

Note

Third party engines are not supported by MySQL. For further information, documentation, installation guides, bug reporting or for any any help or assistance with these engines, please contact the developer of the engine directly.

Third party engines that are known to be available include the following; please see the MySQL Forge links provided for more information:

  • PrimeBase XT (PBXT) — PBXT has been designed for modern, web-based, high concurrency environments.

  • RitmarkFS — RitmarkFS allows you to access and manipulate the filesystem using SQL queries. RitmarkFS also supports filesystem replication and directory change tracking.

  • Distributed Data Engine — The Distributed Data Engine is an Open Source project that is dedicated to provide a Storage Engine for distributed data according to workload statistics.

  • mdbtools — A pluggable storage engine that allows read-only access to Microsoft Access .mdb database files.

  • solidDB for MySQL — solidDB Storage Engine for MySQL is an open source, transactional storage engine for MySQL Server. It is designed for mission-critical implementations that require a robust, transactional database. solidDB Storage Engine for MySQL is a multi-threaded storage engine that supports full ACID compliance with all expected transaction isolation levels, row-level locking, and Multi-Version Concurrency Control (MVCC) with non-blocking reads and writes.

For more information on developing a customer storage engine that can be used with the Pluggable Storage Engine Architecture, see Writing a Custom Storage Engine, in the MySQL Internals manual.

14.3. Setting the Storage Engine

When you create a new table, you can specify which storage engine to use by adding an ENGINE table option to the CREATE TABLE statement:

CREATE TABLE t (i INT) ENGINE = INNODB;

If you omit the ENGINE or TYPE option, the default storage engine is used. Normally, this is MyISAM, but you can change it by using the --default-storage-engine or --default-table-type server startup option, or by setting the default-storage-engine or default-table-type option in the my.cnf configuration file.

You can set the default storage engine to be used during the current session by setting the storage_engine variable:

SET storage_engine=MYISAM;

When MySQL is installed on Windows using the MySQL Configuration Wizard, the InnoDB storage engine can be selected as the default instead of MyISAM. See Section 2.3.4.6, “The Database Usage Dialog”.

To convert a table from one storage engine to another, use an ALTER TABLE statement that indicates the new engine:

ALTER TABLE t ENGINE = MYISAM;

See Section 13.1.7, “CREATE TABLE Syntax”, and Section 13.1.2, “ALTER TABLE Syntax”.

If you try to use a storage engine that is not compiled in or that is compiled in but deactivated, MySQL instead creates a table using the default storage engine, usually MyISAM. This behavior is convenient when you want to copy tables between MySQL servers that support different storage engines. (For example, in a replication setup, perhaps your master server supports transactional storage engines for increased safety, but the slave servers use only non-transactional storage engines for greater speed.)

This automatic substitution of the default storage engine for unavailable engines can be confusing for new MySQL users. A warning is generated whenever a storage engine is automatically changed.

For new tables, MySQL always creates an .frm file to hold the table and column definitions. The table's index and data may be stored in one or more other files, depending on the storage engine. The server creates the .frm file above the storage engine level. Individual storage engines create any additional files required for the tables that they manage. If a table name contains special characters, the names for the table files contain encoded versions of those characters as described in Section 9.2.3, “Mapping of Identifiers to Filenames”.

A database may contain tables of different types. That is, tables need not all be created with the same storage engine.

14.4. The MyISAM Storage Engine

MyISAM is the default storage engine. It is based on the older ISAM code but has many useful extensions. (Note that MySQL 5.1 does not support ISAM.)

Each MyISAM table is stored on disk in three files. The files have names that begin with the table name and have an extension to indicate the file type. An .frm file stores the table format. The data file has an .MYD (MYData) extension. The index file has an .MYI (MYIndex) extension.

To specify explicitly that you want a MyISAM table, indicate that with an ENGINE table option:

CREATE TABLE t (i INT) ENGINE = MYISAM;

Normally, it is unnecesary to use ENGINE to specify the MyISAM storage engine. MyISAM is the default engine unless the default has been changed. To ensure that MyISAM is used in situations where the default might have been changed, include the ENGINE option explicitly.

You can check or repair MyISAM tables with the mysqlcheck client or myisamchk utility. You can also compress MyISAM tables with myisampack to take up much less space. See Section 8.11, “mysqlcheck — A Table Maintenance and Repair Program”, Section 5.10.4.1, “Using myisamchk for Crash Recovery”, and Section 8.6, “myisampack — Generate Compressed, Read-Only MyISAM Tables”.

MyISAM tables have the following characteristics:

  • All data values are stored with the low byte first. This makes the data machine and operating system independent. The only requirements for binary portability are that the machine uses two's-complement signed integers and IEEE floating-point format. These requirements are widely used among mainstream machines. Binary compatibility might not be applicable to embedded systems, which sometimes have peculiar processors.

    There is no significant speed penalty for storing data low byte first; the bytes in a table row normally are unaligned and it takes little more processing to read an unaligned byte in order than in reverse order. Also, the code in the server that fetches column values is not time critical compared to other code.

  • All numeric key values are stored with the high byte first to allow better index compression.

  • Large files (up to 63-bit file length) are supported on filesystems and operating systems that support large files.

  • There is a limit of 232 (~4.295E+09) rows in a MyISAM table. You can increase this limitation if you build MySQL with the --with-big-tables option then the row limitation is increased to (232)2 (1.844E+19) rows. See Section 2.9.2, “Typical configure Options”. Beginning with MySQL 5.0.4 all standard binaries are built with this option.

  • The maximum number of indexes per MyISAM table is 64. This can be changed by recompiling. Beginning with MySQL 5.1.4, you can configure the build by invoking configure with the --with-max-indexes=N option, where N is the maximum number of indexes to permit per MyISAM table. N must be less thann or equal to 128. Before MySQL 5.1.4, you must change the source.

    The maximum number of columns per index is 16.

  • The maximum key length is 1000 bytes. This can also be changed by changing the source and recompiling. For the case of a key longer than 250 bytes, a larger key block size than the default of 1024 bytes is used.

  • When rows are inserted in sorted order (as when you are using an AUTO_INCREMENT column), the index tree is split so that the high node only contains one key. This improves space utilization in the index tree.

  • Internal handling of one AUTO_INCREMENT column per table is supported. MyISAM automatically updates this column for INSERT and UPDATE operations. This makes AUTO_INCREMENT columns faster (at least 10%). Values at the top of the sequence are not reused after being deleted. (When an AUTO_INCREMENT column is defined as the last column of a multiple-column index, reuse of values deleted from the top of a sequence does occur.) The AUTO_INCREMENT value can be reset with ALTER TABLE or myisamchk.

  • Dynamic-sized rows are much less fragmented when mixing deletes with updates and inserts. This is done by automatically combining adjacent deleted blocks and by extending blocks if the next block is deleted.

  • If a table has no free blocks in the middle of the data file, you can INSERT new rows into it at the same time that other threads are reading from the table. (These are known as concurrent inserts.) A free block can occur as a result of deleting rows or an update of a dynamic length row with more data than its current contents. When all free blocks are used up (filled in), future inserts become concurrent again. See Section 7.3.3, “Concurrent Inserts”.

  • You can put the data file and index file on different directories to get more speed with the DATA DIRECTORY and INDEX DIRECTORY table options to CREATE TABLE. See Section 13.1.7, “CREATE TABLE Syntax”.

  • BLOB and TEXT columns can be indexed.

  • NULL values are allowed in indexed columns. This takes 0–1 bytes per key.

  • Each character column can have a different character set. See Chapter 10, Character Set Support.

  • There is a flag in the MyISAM index file that indicates whether the table was closed correctly. If mysqld is started with the --myisam-recover option, MyISAM tables are automatically checked when opened, and are repaired if the table wasn't closed properly.

  • myisamchk marks tables as checked if you run it with the --update-state option. myisamchk --fast checks only those tables that don't have this mark.

  • myisamchk --analyze stores statistics for portions of keys, as well as for entire keys.

  • myisampack can pack BLOB and VARCHAR columns.

MyISAM also supports the following features:

  • Support for a true VARCHAR type; a VARCHAR column starts with a length stored in one or two bytes.

  • Tables with VARCHAR columns may have fixed or dynamic row length.

  • The sum of the lengths of the VARCHAR and CHAR columns in a table may be up to 64KB.

  • A hashed computed index can be used for UNIQUE. This allows you to have UNIQUE on any combination of columns in a table. (However, you cannot search on a UNIQUE computed index.)

Additional resources

14.4.1. MyISAM Startup Options

The following options to mysqld can be used to change the behavior of MyISAM tables. For additional information, see Section 5.2.2, “Command Options”.

  • --myisam-recover=mode

    Set the mode for automatic recovery of crashed MyISAM tables.

  • --delay-key-write=ALL

    Don't flush key buffers between writes for any MyISAM table.

    Note: If you do this, you should not access MyISAM tables from another program (such as from another MySQL server or with myisamchk) when the tables are in use. Doing so risks index corruption. Using --external-locking does not eliminate this risk.

The following system variables affect the behavior of MyISAM tables. For additional information, see Section 5.2.3, “System Variables”.

  • bulk_insert_buffer_size

    The size of the tree cache used in bulk insert optimization. Note: This is a limit per thread!

  • myisam_max_sort_file_size

    The maximum size of the temporary file that MySQL is allowed to use while re-creating a MyISAM index (during REPAIR TABLE, ALTER TABLE, or LOAD DATA INFILE). If the file size would be larger than this value, the index is created using the key cache instead, which is slower. The value is given in bytes.

  • myisam_sort_buffer_size

    Set the size of the buffer used when recovering tables.

Automatic recovery is activated if you start mysqld with the --myisam-recover option. In this case, when the server opens a MyISAM table, it checks whether the table is marked as crashed or whether the open count variable for the table is not 0 and you are running the server with external locking disabled. If either of these conditions is true, the following happens:

  • The server checks the table for errors.

  • If the server finds an error, it tries to do a fast table repair (with sorting and without re-creating the data file).

  • If the repair fails because of an error in the data file (for example, a duplicate-key error), the server tries again, this time re-creating the data file.

  • If the repair still fails, the server tries once more with the old repair option method (write row by row without sorting). This method should be able to repair any type of error and has low disk space requirements.

If the recovery wouldn't be able to recover all rows from previously completed statementas and you didn't specify FORCE in the value of the --myisam-recover option, automatic repair aborts with an error message in the error log:

Error: Couldn't repair table: test.g00pages

If you specify FORCE, a warning like this is written instead:

Warning: Found 344 of 354 rows when repairing ./test/g00pages

Note that if the automatic recovery value includes BACKUP, the recovery process creates files with names of the form tbl_name-datetime.BAK. You should have a cron script that automatically moves these files from the database directories to backup media.

14.4.2. Space Needed for Keys

MyISAM tables use B-tree indexes. You can roughly calculate the size for the index file as (key_length+4)/0.67, summed over all keys. This is for the worst case when all keys are inserted in sorted order and the table doesn't have any compressed keys.

String indexes are space compressed. If the first index part is a string, it is also prefix compressed. Space compression makes the index file smaller than the worst-case figure if a string column has a lot of trailing space or is a VARCHAR column that is not always used to the full length. Prefix compression is used on keys that start with a string. Prefix compression helps if there are many strings with an identical prefix.

In MyISAM tables, you can also prefix compress numbers by specifying the PACK_KEYS=1 table option when you create the table. Numbers are stored with the high byte first, so this helps when you have many integer keys that have an identical prefix.

14.4.3. MyISAM Table Storage Formats

MyISAM supports three different storage formats. Two of them, fixed and dynamic format, are chosen automatically depending on the type of columns you are using. The third, compressed format, can be created only with the myisampack utility.

When you use CREATE TABLE or ALTER TABLE for a table that has no BLOB or TEXT columns, you can force the table format to FIXED or DYNAMIC with the ROW_FORMAT table option.

You can decompress tables by specifying ROW_FORMAT=DEFAULT with ALTER TABLE.

See Section 13.1.7, “CREATE TABLE Syntax”, for information about ROW_FORMAT.

14.4.3.1. Static (Fixed-Length) Table Characteristics

Static format is the default for MyISAM tables. It is used when the table contains no variable-length columns (VARCHAR, VARBINARY, BLOB, or TEXT). Each row is stored using a fixed number of bytes.

Of the three MyISAM storage formats, static format is the simplest and most secure (least subject to corruption). It is also the fastest of the on-disk formats due to the ease with which rows in the data file can be found on disk: To look up a row based on a row number in the index, multiply the row number by the row length to calculate the row position. Also, when scanning a table, it is very easy to read a constant number of rows with each disk read operation.

The security is evidenced if your computer crashes while the MySQL server is writing to a fixed-format MyISAM file. In this case, myisamchk can easily determine where each row starts and ends, so it can usually reclaim all rows except the partially written one. Note that MyISAM table indexes can always be reconstructed based on the data rows.

Note

Fixed-length row format is only available for tables without BLOB or TEXT columns. Creating a table with these columns with an explicit ROW_FORMAT clause will not raise an error or warning; the format specification will be ignored.

Static-format tables have these characteristics:

  • CHAR and VARCHAR columns are space-padded to the specified column width, although the column type is not altered. BINARY and VARBINARY columns are padded with 0x00 bytes to the column width.

  • Very quick.

  • Easy to cache.

  • Easy to reconstruct after a crash, because rows are located in fixed positions.

  • Reorganization is unnecessary unless you delete a huge number of rows and want to return free disk space to the operating system. To do this, use OPTIMIZE TABLE or myisamchk -r.

  • Usually require more disk space than dynamic-format tables.

14.4.3.2. Dynamic Table Characteristics

Dynamic storage format is used if a MyISAM table contains any variable-length columns (VARCHAR, VARBINARY, BLOB, or TEXT), or if the table was created with the ROW_FORMAT=DYNAMIC table option.

Dynamic format is a little more complex than static format because each row has a header that indicates how long it is. A row can become fragmented (stored in non-contiguous pieces) when it is made longer as a result of an update.

You can use OPTIMIZE TABLE or myisamchk -r to defragment a table. If you have fixed-length columns that you access or change frequently in a table that also contains some variable-length columns, it might be a good idea to move the variable-length columns to other tables just to avoid fragmentation.

Dynamic-format tables have these characteristics:

  • All string columns are dynamic except those with a length less than four.

  • Each row is preceded by a bitmap that indicates which columns contain the empty string (for string columns) or zero (for numeric columns). Note that this does not include columns that contain NULL values. If a string column has a length of zero after trailing space removal, or a numeric column has a value of zero, it is marked in the bitmap and not saved to disk. Non-empty strings are saved as a length byte plus the string contents.

  • Much less disk space usually is required than for fixed-length tables.

  • Each row uses only as much space as is required. However, if a row becomes larger, it is split into as many pieces as are required, resulting in row fragmentation. For example, if you update a row with information that extends the row length, the row becomes fragmented. In this case, you may have to run OPTIMIZE TABLE or myisamchk -r from time to time to improve performance. Use myisamchk -ei to obtain table statistics.

  • More difficult than static-format tables to reconstruct after a crash, because rows may be fragmented into many pieces and links (fragments) may be missing.

  • The expected row length for dynamic-sized rows is calculated using the following expression:

    3
    + (number of columns + 7) / 8
    + (number of char columns)
    + (packed size of numeric columns)
    + (length of strings)
    + (number of NULL columns + 7) / 8
    

    There is a penalty of 6 bytes for each link. A dynamic row is linked whenever an update causes an enlargement of the row. Each new link is at least 20 bytes, so the next enlargement probably goes in the same link. If not, another link is created. You can find the number of links using myisamchk -ed. All links may be removed with OPTIMIZE TABLE or myisamchk -r.

14.4.3.3. Compressed Table Characteristics

Compressed storage format is a read-only format that is generated with the myisampack tool. Compressed tables can be uncompressed with myisamchk.

Compressed tables have the following characteristics:

  • Compressed tables take very little disk space. This minimizes disk usage, which is helpful when using slow disks (such as CD-ROMs).

  • Each row is compressed separately, so there is very little access overhead. The header for a row takes up one to three bytes depending on the biggest row in the table. Each column is compressed differently. There is usually a different Huffman tree for each column. Some of the compression types are:

    • Suffix space compression.

    • Prefix space compression.

    • Numbers with a value of zero are stored using one bit.

    • If values in an integer column have a small range, the column is stored using the smallest possible type. For example, a BIGINT column (eight bytes) can be stored as a TINYINT column (one byte) if all its values are in the range from -128 to 127.

    • If a column has only a small set of possible values, the data type is converted to ENUM.

    • A column may use any combination of the preceding compression types.

  • Can be used for fixed-length or dynamic-length rows.

Note.  While a compressed table is read-only, and you cannot therefore update or add rows in the table, DDL (Data Definition Language) operations are still valid. For example, you may still use DROP to drop the table, and TRUNCATE to empty the table.

14.4.4. MyISAM Table Problems

The file format that MySQL uses to store data has been extensively tested, but there are always circumstances that may cause database tables to become corrupted. The following discussion describes how this can happen and how to handle it.

14.4.4.1. Corrupted MyISAM Tables

Even though the MyISAM table format is very reliable (all changes to a table made by an SQL statement are written before the statement returns), you can still get corrupted tables if any of the following events occur:

  • The mysqld process is killed in the middle of a write.

  • An unexpected computer shutdown occurs (for example, the computer is turned off).

  • Hardware failures.

  • You are using an external program (such as myisamchk) to modify a table that is being modified by the server at the same time.

  • A software bug in the MySQL or MyISAM code.

Typical symptoms of a corrupt table are:

  • You get the following error while selecting data from the table:

    Incorrect key file for table: '...'. Try to repair it
    
  • Queries don't find rows in the table or return incomplete results.

You can check the health of a MyISAM table using the CHECK TABLE statement, and repair a corrupted MyISAM table with REPAIR TABLE. When mysqld is not running, you can also check or repair a table with the myisamchk command. See Section 13.5.2.3, “CHECK TABLE Syntax”, Section 13.5.2.6, “REPAIR TABLE Syntax”, and Section 8.4, “myisamchk — MyISAM Table-Maintenance Utility”.

If your tables become corrupted frequently, you should try to determine why this is happening. The most important thing to know is whether the table became corrupted as a result of a server crash. You can verify this easily by looking for a recent restarted mysqld message in the error log. If there is such a message, it is likely that table corruption is a result of the server dying. Otherwise, corruption may have occurred during normal operation. This is a bug. You should try to create a reproducible test case that demonstrates the problem. See Section B.4.2, “What to Do If MySQL Keeps Crashing”, and Section F.1.6, “Making a Test Case If You Experience Table Corruption”.

14.4.4.2. Problems from Tables Not Being Closed Properly

Each MyISAM index file (.MYI file) has a counter in the header that can be used to check whether a table has been closed properly. If you get the following warning from CHECK TABLE or myisamchk, it means that this counter has gone out of sync:

clients are using or haven't closed the table properly

This warning doesn't necessarily mean that the table is corrupted, but you should at least check the table.

The counter works as follows:

  • The first time a table is updated in MySQL, a counter in the header of the index files is incremented.

  • The counter is not changed during further updates.

  • When the last instance of a table is closed (because a FLUSH TABLES operation was performed or because there is no room in the table cache), the counter is decremented if the table has been updated at any point.

  • When you repair the table or check the table and it is found to be okay, the counter is reset to zero.

  • To avoid problems with interaction with other processes that might check the table, the counter is not decremented on close if it was zero.

In other words, the counter can become incorrect only under these conditions:

  • A MyISAM table is copied without first issuing LOCK TABLES and FLUSH TABLES.

  • MySQL has crashed between an update and the final close. (Note that the table may still be okay, because MySQL always issues writes for everything between each statement.)

  • A table was modified by myisamchk --recover or myisamchk --update-state at the same time that it was in use by mysqld.

  • Multiple mysqld servers are using the table and one server performed a REPAIR TABLE or CHECK TABLE on the table while it was in use by another server. In this setup, it is safe to use CHECK TABLE, although you might get the warning from other servers. However, REPAIR TABLE should be avoided because when one server replaces the data file with a new one, this is not known to the other servers.

    In general, it is a bad idea to share a data directory among multiple servers. See Section 5.13, “Running Multiple MySQL Servers on the Same Machine”, for additional discussion.

14.5. The InnoDB Storage Engine

14.5.1. InnoDB Overview

InnoDB provides MySQL with a transaction-safe (ACID compliant) storage engine that has commit, rollback, and crash recovery capabilities. InnoDB does locking on the row level and also provides an Oracle-style consistent non-locking read in SELECT statements. These features increase multi-user concurrency and performance. There is no need for lock escalation in InnoDB because row-level locks fit in very little space. InnoDB also supports FOREIGN KEY constraints. You can freely mix InnoDB tables with tables from other MySQL storage engines, even within the same statement.

InnoDB has been designed for maximum performance when processing large data volumes. Its CPU efficiency is probably not matched by any other disk-based relational database engine.

Fully integrated with MySQL Server, the InnoDB storage engine maintains its own buffer pool for caching data and indexes in main memory. InnoDB stores its tables and indexes in a tablespace, which may consist of several files (or raw disk partitions). This is different from, for example, MyISAM tables where each table is stored using separate files. InnoDB tables can be of any size even on operating systems where file size is limited to 2GB.

InnoDB is included in binary distributions by default. The Windows Essentials installer makes InnoDB the MySQL default storage engine on Windows.

InnoDB is used in production at numerous large database sites requiring high performance. The famous Internet news site Slashdot.org runs on InnoDB. Mytrix, Inc. stores over 1TB of data in InnoDB, and another site handles an average load of 800 inserts/updates per second in InnoDB.

InnoDB is published under the same GNU GPL License Version 2 (of June 1991) as MySQL. For more information on MySQL licensing, see http://www.mysql.com/company/legal/licensing/.

Additional resources

14.5.2. InnoDB Contact Information

Contact information for Innobase Oy, producer of the InnoDB engine:

Web site: http://www.innodb.com/
Email: 
Phone: +358-9-6969 3250 (office)
       +358-40-5617367 (mobile)

Innobase Oy Inc.
World Trade Center Helsinki
Aleksanterinkatu 17
P.O.Box 800
00101 Helsinki
Finland

14.5.3. InnoDB Configuration

The InnoDB storage engine is enabled by default. If you don't want to use InnoDB tables, you can add the skip-innodb option to your MySQL option file.

Note: InnoDB provides MySQL with a transaction-safe (ACID compliant) storage engine that has commit, rollback, and crash recovery capabilities. However, it cannot do so if the underlying operating system or hardware does not work as advertised. Many operating systems or disk subsystems may delay or reorder write operations to improve performance. On some operating systems, the very system call that should wait until all unwritten data for a file has been flushed — fsync() — might actually return before the data has been flushed to stable storage. Because of this, an operating system crash or a power outage may destroy recently committed data, or in the worst case, even corrupt the database because of write operations having been reordered. If data integrity is important to you, you should perform some “pull-the-plug” tests before using anything in production. On Mac OS X 10.3 and up, InnoDB uses a special fcntl() file flush method. Under Linux, it is advisable to disable the write-back cache.

On ATAPI hard disks, a command such hdparm -W0 /dev/hda may work to disable the write-back cache. Beware that some drives or disk controllers may be unable to disable the write-back cache.

Two important disk-based resources managed by the InnoDB storage engine are its tablespace data files and its log files.

Note: If you specify no InnoDB configuration options, MySQL creates an auto-extending 10MB data file named ibdata1 and two 5MB log files named ib_logfile0 and ib_logfile1 in the MySQL data directory. To get good performance, you should explicitly provide InnoDB parameters as discussed in the following examples. Naturally, you should edit the settings to suit your hardware and requirements.

The examples shown here are representative. See Section 14.5.4, “InnoDB Startup Options and System Variables” for additional information about InnoDB-related configuration parameters.

To set up the InnoDB tablespace files, use the innodb_data_file_path option in the [mysqld] section of the my.cnf option file. On Windows, you can use my.ini instead. The value of innodb_data_file_path should be a list of one or more data file specifications. If you name more than one data file, separate them by semicolon (‘;’) characters:

innodb_data_file_path=datafile_spec1[;datafile_spec2]...

For example, a setting that explicitly creates a tablespace having the same characteristics as the default is as follows:

[mysqld]
innodb_data_file_path=ibdata1:10M:autoextend

This setting configures a single 10MB data file named ibdata1 that is auto-extending. No location for the file is given, so by default, InnoDB creates it in the MySQL data directory.

Sizes are specified using M or G suffix letters to indicate units of MB or GB.

A tablespace containing a fixed-size 50MB data file named ibdata1 and a 50MB auto-extending file named ibdata2 in the data directory can be configured like this:

[mysqld]
innodb_data_file_path=ibdata1:50M;ibdata2:50M:autoextend

The full syntax for a data file specification includes the filename, its size, and several optional attributes:

file_name:file_size[:autoextend[:max:max_file_size]]

The autoextend attribute and those following can be used only for the last data file in the innodb_data_file_path line.

If you specify the autoextend option for the last data file, InnoDB extends the data file if it runs out of free space in the tablespace. The increment is 8MB at a time by default. It can be modified by changing the innodb_autoextend_increment system variable.

If the disk becomes full, you might want to add another data file on another disk. Instructions for reconfiguring an existing tablespace are given in Section 14.5.7, “Adding and Removing InnoDB Data and Log Files”.

InnoDB is not aware of the filesystem maximum file size, so be cautious on filesystems where the maximum file size is a small value such as 2GB. To specify a maximum size for an auto-extending data file, use the max attribute. The following configuration allows ibdata1 to grow up to a limit of 500MB:

[mysqld]
innodb_data_file_path=ibdata1:10M:autoextend:max:500M

InnoDB creates tablespace files in the MySQL data directory by default. To specify a location explicitly, use the innodb_data_home_dir option. For example, to use two files named ibdata1 and ibdata2 but create them in the /ibdata directory, configure InnoDB like this:

[mysqld]
innodb_data_home_dir = /ibdata
innodb_data_file_path=ibdata1:50M;ibdata2:50M:autoextend

Note: InnoDB does not create directories, so make sure that the /ibdata directory exists before you start the server. This is also true of any log file directories that you configure. Use the Unix or DOS mkdir command to create any necessary directories.

InnoDB forms the directory path for each data file by textually concatenating the value of innodb_data_home_dir to the data file name, adding a pathname separator (slash or backslash) between values if necessary. If the innodb_data_home_dir option is not mentioned in my.cnf at all, the default value is the “dot” directory ./, which means the MySQL data directory. (The MySQL server changes its current working directory to its data directory when it begins executing.)

If you specify innodb_data_home_dir as an empty string, you can specify absolute paths for the data files listed in the innodb_data_file_path value. The following example is equivalent to the preceding one:

[mysqld]
innodb_data_home_dir =
innodb_data_file_path=/ibdata/ibdata1:50M;/ibdata/ibdata2:50M:autoextend

A simple my.cnf example. Suppose that you have a computer with 128MB RAM and one hard disk. The following example shows possible configuration parameters in my.cnf or my.ini for InnoDB, including the autoextend attribute. The example suits most users, both on Unix and Windows, who do not want to distribute InnoDB data files and log files onto several disks. It creates an auto-extending data file ibdata1 and two InnoDB log files ib_logfile0 and ib_logfile1 in the MySQL data directory.

[mysqld]
# You can write your other MySQL server options here
# ...
# Data files must be able to hold your data and indexes.
# Make sure that you have enough free disk space.
innodb_data_file_path = ibdata1:10M:autoextend
#
# Set buffer pool size to 50-80% of your computer's memory
innodb_buffer_pool_size=70M
innodb_additional_mem_pool_size=10M
#
# Set the log file size to about 25% of the buffer pool size
innodb_log_file_size=20M
innodb_log_buffer_size=8M
#
innodb_flush_log_at_trx_commit=1

Make sure that the MySQL server has the proper access rights to create files in the data directory. More generally, the server must have access rights in any directory where it needs to create data files or log files.

Note that data files must be less than 2GB in some filesystems. The combined size of the log files must be less than 4GB. The combined size of data files must be at least 10MB.

When you create an InnoDB tablespace for the first time, it is best that you start the MySQL server from the command prompt. InnoDB then prints the information about the database creation to the screen, so you can see what is happening. For example, on Windows, if mysqld is located in C:\Program Files\MySQL\MySQL Server 5.1\bin, you can start it like this:

C:\> "C:\Program Files\MySQL\MySQL Server 5.1\bin\mysqld" --console

If you do not send server output to the screen, check the server's error log to see what InnoDB prints during the startup process.

See Section 14.5.5, “Creating the InnoDB Tablespace”, for an example of what the information displayed by InnoDB should look like.

You can place InnoDB options in the [mysqld] group of any option file that your server reads when it starts. The locations for option files are described in Section 4.3.2, “Using Option Files”.

If you installed MySQL on Windows using the installation and configuration wizards, the option file will be the my.ini file located in your MySQL installation directory. See Section 2.3.4.14, “The Location of the my.ini File”.

If your PC uses a boot loader where the C: drive is not the boot drive, your only option is to use the my.ini file in your Windows directory (typically C:\WINDOWS or C:\WINNT). You can use the SET command at the command prompt in a console window to print the value of WINDIR:

C:\> SET WINDIR
windir=C:\WINDOWS

If you want to make sure that mysqld reads options only from a specific file, you can use the --defaults-file option as the first option on the command line when starting the server:

mysqld --defaults-file=your_path_to_my_cnf

An advanced my.cnf example. Suppose that you have a Linux computer with 2GB RAM and three 60GB hard disks at directory paths /, /dr2 and /dr3. The following example shows possible configuration parameters in my.cnf for InnoDB.

[mysqld]
# You can write your other MySQL server options here
# ...
innodb_data_home_dir =
#
# Data files must be able to hold your data and indexes
innodb_data_file_path = /db/ibdata1:2000M;/dr2/db/ibdata2:2000M:autoextend
#
# Set buffer pool size to 50-80% of your computer's memory,
# but make sure on Linux x86 total memory usage is < 2GB
innodb_buffer_pool_size=1G
innodb_additional_mem_pool_size=20M
innodb_log_group_home_dir = /dr3/iblogs
#
innodb_log_files_in_group = 2
#
# Set the log file size to about 25% of the buffer pool size
innodb_log_file_size=250M
innodb_log_buffer_size=8M
#
innodb_flush_log_at_trx_commit=1
innodb_lock_wait_timeout=50
#
# Uncomment the next lines if you want to use them
#innodb_thread_concurrency=5

In some cases, database performance improves the if all data is not placed on the same physical disk. Putting log files on a different disk from data is very often beneficial for performance. The example illustrates how to do this. It places the two data files on different disks and places the log files on the third disk. InnoDB fills the tablespace beginning with the first data file. You can also use raw disk partitions (raw devices) as InnoDB data files, which may speed up I/O. See Section 14.5.3.2, “Using Raw Devices for the Shared Tablespace”.

Warning: On 32-bit GNU/Linux x86, you must be careful not to set memory usage too high. glibc may allow the process heap to grow over thread stacks, which crashes your server. It is a risk if the value of the following expression is close to or exceeds 2GB:

innodb_buffer_pool_size
+ key_buffer_size
+ max_connections*(sort_buffer_size+read_buffer_size+binlog_cache_size)
+ max_connections*2MB

Each thread uses a stack (often 2MB, but only 256KB in MySQL AB binaries) and in the worst case also uses sort_buffer_size + read_buffer_size additional memory.

By compiling MySQL yourself, you can use up to 64GB of physical memory in 32-bit Windows. See the description for innodb_buffer_pool_awe_mem_mb in Section 14.5.4, “InnoDB Startup Options and System Variables”.

How to tune other mysqld server parameters? The following values are typical and suit most users:

[mysqld]
skip-external-locking
max_connections=200
read_buffer_size=1M
sort_buffer_size=1M
#
# Set key_buffer to 5 - 50% of your RAM depending on how much
# you use MyISAM tables, but keep key_buffer_size + InnoDB
# buffer pool size < 80% of your RAM
key_buffer_size=value

14.5.3.1. Using Per-Table Tablespaces

You can store each InnoDB table and its indexes in its own file. This feature is called “multiple tablespaces” because in effect each table has its own tablespace.

Using multiple tablespaces can be beneficial to users who want to move specific tables to separate physical disks or who wish to restore backups of single tables quickly without interrupting the use of the remaining InnoDB tables.

You can enable multiple tablespaces by adding this line to the [mysqld] section of my.cnf:

[mysqld]
innodb_file_per_table

After restarting the server, InnoDB stores each newly created table into its own file tbl_name.ibd in the database directory where the table belongs. This is similar to what the MyISAM storage engine does, but MyISAM divides the table into a data file tbl_name.MYD and the index file tbl_name.MYI. For InnoDB, the data and the indexes are stored together in the .ibd file. The tbl_name.frm file is still created as usual.

If you remove the innodb_file_per_table line from my.cnf and restart the server, InnoDB creates tables inside the shared tablespace files again.

innodb_file_per_table affects only table creation, not access to existing tables. If you start the server with this option, new tables are created using .ibd files, but you can still access tables that exist in the shared tablespace. If you remove the option and restart the server, new tables are created in the shared tablespace, but you can still access any tables that were created using multiple tablespaces.

Note: InnoDB always needs the shared tablespace because it puts its internal data dictionary and undo logs there. The .ibd files are not sufficient for InnoDB to operate.

Note: You cannot freely move .ibd files between database directories as you can with MyISAM table files. This is because the table definition that is stored in the InnoDB shared tablespace includes the database name, and because InnoDB must preserve the consistency of transaction IDs and log sequence numbers.

To move an .ibd file and the associated table from one database to another, use a RENAME TABLE statement:

RENAME TABLE db1.tbl_name TO db2.tbl_name;

If you have a “clean” backup of an .ibd file, you can restore it to the MySQL installation from which it originated as follows:

  1. Issue this ALTER TABLE statement:

    ALTER TABLE tbl_name DISCARD TABLESPACE;
    

    Caution: This statement deletes the current .ibd file.

  2. Put the backup .ibd file back in the proper database directory.

  3. Issue this ALTER TABLE statement:

    ALTER TABLE tbl_name IMPORT TABLESPACE;
    

In this context, a “clean.ibd file backup means:

  • There are no uncommitted modifications by transactions in the .ibd file.

  • There are no unmerged insert buffer entries in the .ibd file.

  • Purge has removed all delete-marked index records from the .ibd file.

  • mysqld has flushed all modified pages of the .ibd file from the buffer pool to the file.

You can make a clean backup .ibd file using the following method:

  1. Stop all activity from the mysqld server and commit all transactions.

  2. Wait until SHOW ENGINE INNODB STATUS shows that there are no active transactions in the database, and the main thread status of InnoDB is Waiting for server activity. Then you can make a copy of the .ibd file.

Another method for making a clean copy of an .ibd file is to use the commercial InnoDB Hot Backup tool:

  1. Use InnoDB Hot Backup to back up the InnoDB installation.

  2. Start a second mysqld server on the backup and let it clean up the .ibd files in the backup.

14.5.3.2. Using Raw Devices for the Shared Tablespace

You can use raw disk partitions as data files in the shared tablespace. By using a raw disk, you can perform non-buffered I/O on Windows and on some Unix systems without filesystem overhead, which may improve performance.

When you create a new data file, you must put the keyword newraw immediately after the data file size in innodb_data_file_path. The partition must be at least as large as the size that you specify. Note that 1MB in InnoDB is 1024 × 1024 bytes, whereas 1MB in disk specifications usually means 1,000,000 bytes.

[mysqld]
innodb_data_home_dir=
innodb_data_file_path=/dev/hdd1:3Gnewraw;/dev/hdd2:2Gnewraw

The next time you start the server, InnoDB notices the newraw keyword and initializes the new partition. However, do not create or change any InnoDB tables yet. Otherwise, when you next restart the server, InnoDB reinitializes the partition and your changes are lost. (As a safety measure InnoDB prevents users from modifying data when any partition with newraw is specified.)

After InnoDB has initialized the new partition, stop the server, change newraw in the data file specification to raw:

[mysqld]
innodb_data_home_dir=
innodb_data_file_path=/dev/hdd1:5Graw;/dev/hdd2:2Graw

Then restart the server and InnoDB allows changes to be made.

On Windows, you can allocate a disk partition as a data file like this:

[mysqld]
innodb_data_home_dir=
innodb_data_file_path=//./D::10Gnewraw

The //./ corresponds to the Windows syntax of \\.\ for accessing physical drives.

When you use raw disk partitions, be sure that they have permissions that allow read and write access by the account used for running the MySQL server.

14.5.4. InnoDB Startup Options and System Variables

This section describes the InnoDB-related command options and system variables. System variables that are true or false can be enabled at server startup by naming them, or disabled by using a skip- prefix. For example, to enable or disable InnoDB checksums, you can use --innodb_checksums or --skip-innodb_checksums on the command line, or innodb_checksums or skip-innodb_checksums in an option file. System variables that take a numeric value can be specified as --var_name=value on the command line or as var_name=value in option files. For more information on specifying options and system variables, see Section 4.3, “Specifying Program Options”. Many of the system variables can be changed at runtime (see Section 5.2.4.2, “Dynamic System Variables”).

InnoDB command options:

  • --innodb

    Enables the InnoDB storage engine, if the server was compiled with InnoDB support. Use --skip-innodb to disable InnoDB.

  • --innodb_status_file

    Causes InnoDB to create a file named <datadir>/innodb_status.<pid> in the MySQL data directory. InnoDB periodically writes the output of SHOW ENGINE INNODB STATUS to this file.

InnoDB system variables:

  • innodb_additional_mem_pool_size

    The size in bytes of a memory pool InnoDB uses to store data dictionary information and other internal data structures. The more tables you have in your application, the more memory you need to allocate here. If InnoDB runs out of memory in this pool, it starts to allocate memory from the operating system and writes warning messages to the MySQL error log. The default value is 1MB.

  • innodb_autoextend_increment

    The increment size (in MB) for extending the size of an auto-extending tablespace when it becomes full. The default value is 8.

  • innodb_buffer_pool_awe_mem_mb

    The size of the buffer pool (in MB), if it is placed in the AWE memory. This is relevant only in 32-bit Windows. If your 32-bit Windows operating system supports more than 4GB memory, using so-called “Address Windowing Extensions,” you can allocate the InnoDB buffer pool into the AWE physical memory using this variable. The maximum possible value for this variable is 63000. If it is greater than 0, innodb_buffer_pool_size is the window in the 32-bit address space of mysqld where InnoDB maps that AWE memory. A good value for innodb_buffer_pool_size is 500MB.

    To take advantage of AWE memory, you will need to recompile MySQL yourself. The current project settings needed for doing this can be found in the storage/innobase/os/os0proj.c source file.

  • innodb_buffer_pool_size

    The size in bytes of the memory buffer InnoDB uses to cache data and indexes of its tables. The larger you set this value, the less disk I/O is needed to access data in tables. On a dedicated database server, you may set this to up to 80% of the machine physical memory size. However, do not set it too large because competition for physical memory might cause paging in the operating system.

  • innodb_checksums

    InnoDB can use checksum validation on all pages read from the disk to ensure extra fault tolerance against broken hardware or data files. This validation is enabled by default. However, under some rare circumstances (such as when running benchmarks) this extra safety feature is unneeded and can be disabled with --skip-innodb-checksums.

  • innodb_commit_concurrency

    The number of threads that can commit at the same time. A value of 0 disables concurrency control.

  • innodb_concurrency_tickets

    The number of threads that can enter InnoDB concurrently is determined by the innodb_thread_concurrency variable. A thread is placed in a queue when it tries to enter InnoDB if the number of threads has already reached the concurrency limit. When a thread is allowed to enter InnoDB, it is given a number of “free tickets” equal to the value of innodb_concurrency_tickets, and the thread can enter and leave InnoDB freely until it has used up its tickets. After that point, the thread again becomes subject to the concurrency check (and possible queuing) the next time it tries to enter InnoDB.

  • innodb_data_file_path

    The paths to individual data files and their sizes. The full directory path to each data file is formed by concatenating innodb_data_home_dir to each path specified here. The file sizes are specified in MB or GB (1024MB) by appending M or G to the size value. The sum of the sizes of the files must be at least 10MB. If you do not specify innodb_data_file_path, the default behavior is to create a single 10MB auto-extending data file named ibdata1. The size limit of individual files is determined by your operating system. You can set the file size to more than 4GB on those operating systems that support big files. You can also use raw disk partitions as data files. See Section 14.5.3.2, “Using Raw Devices for the Shared Tablespace”.

  • innodb_data_home_dir

    The common part of the directory path for all InnoDB data files. If you do not set this value, the default is the MySQL data directory. You can specify the value as an empty string, in which case you can use absolute file paths in innodb_data_file_path.

  • innodb_doublewrite

    By default, InnoDB stores all data twice, first to the doublewrite buffer, and then to the actual data files. This variable is enabled by default. It can be turned off with --skip-innodb_doublewrite for benchmarks or cases when top performance is needed rather than concern for data integrity or possible failures.

  • innodb_fast_shutdown

    If you set this variable to 0, InnoDB does a full purge and an insert buffer merge before a shutdown. These operations can take minutes, or even hours in extreme cases. If you set this variable to 1, InnoDB skips these operations at shutdown. The default value is 1. If you set it to 2, InnoDB will just flush its logs and then shut down cold, as if MySQL had crashed; no committed transaction will be lost, but crash recovery will be done at the next startup. A value of 2 cannot be used on NetWare.

  • innodb_file_io_threads

    The number of file I/O threads in InnoDB. Normally, this should be left at the default value of 4, but disk I/O on Windows may benefit from a larger number. On Unix, increasing the number has no effect; InnoDB always uses the default value.

  • innodb_file_per_table

    If this variable is enabled, InnoDB creates each new table using its own .ibd file for storing data and indexes, rather than in the shared tablespace. The default is to create tables in the shared tablespace. See Section 14.5.3.1, “Using Per-Table Tablespaces”.

  • innodb_flush_log_at_trx_commit

    When innodb_flush_log_at_trx_commit is set to 0, the log buffer is written out to the log file once per second and the flush to disk operation is performed on the log file, but nothing is done at a transaction commit. When this value is 1 (the default), the log buffer is written out to the log file at each transaction commit and the flush to disk operation is performed on the log file. When set to 2, the log buffer is written out to the file at each commit, but the flush to disk operation is not performed on it. However, the flushing on the log file takes place once per second also when the value is 2. Note that the once-per-second flushing is not 100% guaranteed to happen every second, due to process scheduling issues.

    The default value of this variable is 1, which is the value that is required for ACID compliance. You can achieve better performance by setting the value different from 1, but then you can lose at most one second worth of transactions in a crash. If you set the value to 0, then any mysqld process crash can erase the last second of transactions. If you set the value to 2, then only an operating system crash or a power outage can erase the last second of transactions. However, InnoDB's crash recovery is not affected and thus crash recovery does work regardless of the value. Note that many operating systems and some disk hardware fool the flush-to-disk operation. They may tell mysqld that the flush has taken place, even though it has not. Then the durability of transactions is not guaranteed even with the setting 1, and in the worst case a power outage can even corrupt the InnoDB database. Using a battery-backed disk cache in the SCSI disk controller or in the disk itself speeds up file flushes, and makes the operation safer. You can also try using the Unix command hdparm to disable the caching of disk writes in hardware caches, or use some other command specific to the hardware vendor.

    Note: For the greatest possible durability and consistency in a replication setup using InnoDB with transactions, you should use innodb_flush_log_at_trx_commit=1 and sync_binlog=1 in your master server my.cnf file.

  • innodb_flush_method

    If set to fdatasync (the default), InnoDB uses fsync() to flush both the data and log files. If set to O_DSYNC, InnoDB uses O_SYNC to open and flush the log files, but uses fsync() to flush the data files. If O_DIRECT is specified (available on some GNU/Linux versions), InnoDB uses O_DIRECT to open the data files, and uses fsync() to flush both the data and log files. Note that InnoDB uses fsync() instead of fdatasync(), and it does not use O_DSYNC by default because there have been problems with it on many varieties of Unix. This variable is relevant only for Unix. On Windows, the flush method is always async_unbuffered and cannot be changed.

    Different values of this variable can have a marked effect on InnoDB performance. For example, on some systems where InnoDB data and log files are located on a SAN, it has been found that setting innodb_flush_method to O_DIRECT can degrade performance of simple SELECT statements by a factor of three.

  • innodb_force_recovery

    The crash recovery mode. Warning: This variable should be set greater than 0 only in an emergency situation when you want to dump your tables from a corrupt database! Possible values are from 1 to 6. The meanings of these values are described in Section 14.5.8.1, “Forcing InnoDB Recovery”. As a safety measure, InnoDB prevents any changes to its data when this variable is greater than 0.

  • innodb_lock_wait_timeout

    The timeout in seconds an InnoDB transaction may wait for a lock before being rolled back. InnoDB automatically detects transaction deadlocks in its own lock table and rolls back the transaction. InnoDB notices locks set using the LOCK TABLES statement. The default is 50 seconds.

  • innodb_locks_unsafe_for_binlog

    This variable controls next-key locking in InnoDB searches and index scans. By default, this variable is 0 (disabled), which means that next-key locking is enabled.

    Normally, InnoDB uses an algorithm called next-key locking. InnoDB performs row-level locking in such a way that when it searches or scans a table index, it sets shared or exclusive locks on any index records it encounters. Thus, the row-level locks are actually index record locks. The locks that InnoDB sets on index records also affect the “gap” preceding that index record. If a user has a shared or exclusive lock on record R in an index, another user cannot insert a new index record immediately before R in the order of the index. Enabling this variable causes InnoDB not to use next-key locking in searches or index scans. Next-key locking is still used to ensure foreign key constraints and duplicate key checking. Note that enabling this variable may cause phantom problems: Suppose that you want to read and lock all children from the child table with an identifier value larger than 100, with the intention of updating some column in the selected rows later:

    SELECT * FROM child WHERE id > 100 FOR UPDATE;
    

    Suppose that there is an index on the id column. The query scans that index starting from the first record where id is greater than 100. If the locks set on the index records do not lock out inserts made in the gaps, another client can insert a new row into the table. If you execute the same SELECT within the same transaction, you see a new row in the result set returned by the query. This also means that if new items are added to the database, InnoDB does not guarantee serializability. Therefore, if this variable is enabled, InnoDB guarantees at most isolation level READ COMMITTED. (Conflict serializability is still guaranteed.)

    Enabling this variable has an additional effect: InnoDB in an UPDATE or a DELETE only locks rows that it updates or deletes. This greatly reduces the probability of deadlocks, but they can happen. Note that enabling this variable still does not allow operations such as UPDATE to overtake other similar operations (such as another UPDATE) even in the case when they affect different rows. Consider the following example, beginning with this table:

    CREATE TABLE A(A INT NOT NULL, B INT) ENGINE = InnoDB;
    INSERT INTO A VALUES (1,2),(2,3),(3,2),(4,3),(5,2);
    COMMIT;
    

    Suppose that one client executes these statements:

    SET AUTOCOMMIT = 0;
    UPDATE A SET B = 5 WHERE B = 3;
    

    Then suppose that another client executes these statements following those of the first client:

    SET AUTOCOMMIT = 0;
    UPDATE A SET B = 4 WHERE B = 2;
    

    In this case, the second UPDATE must wait for a commit or rollback of the first UPDATE. The first UPDATE has an exclusive lock on row (2,3), and the second UPDATE while scanning rows also tries to acquire an exclusive lock for the same row, which it cannot have. This is because UPDATE two first acquires an exclusive lock on a row and then determines whether the row belongs to the result set. If not, it releases the unnecessary lock, when the innodb_locks_unsafe_for_binlog variable is enabled.

    Therefore, InnoDB executes UPDATE one as follows:

    x-lock(1,2)
    unlock(1,2)
    x-lock(2,3)
    update(2,3) to (2,5)
    x-lock(3,2)
    unlock(3,2)
    x-lock(4,3)
    update(4,3) to (4,5)
    x-lock(5,2)
    unlock(5,2)
    

    InnoDB executes UPDATE two as follows:

    x-lock(1,2)
    update(1,2) to (1,4)
    x-lock(2,3) - wait for query one to commit or rollback
    
  • innodb_log_archive

    Whether to log InnoDB archive files. This variable is present for historical reasons, but is unused. Recovery from a backup is done by MySQL using its own log files, so there is no need to archive InnoDB log files. The default for this variable is 0.

  • innodb_log_buffer_size

    The size in bytes of the buffer that InnoDB uses to write to the log files on disk. Sensible values range from 1MB to 8MB. The default is 1MB. A large log buffer allows large transactions to run without a need to write the log to disk before the transactions commit. Thus, if you have big transactions, making the log buffer larger saves disk I/O.

  • innodb_log_file_size

    The size in bytes of each log file in a log group. The combined size of log files must be less than 4GB on 32-bit computers. The default is 5MB. Sensible values range from 1MB to 1/N-th of the size of the buffer pool, where N is the number of log files in the group. The larger the value, the less checkpoint flush activity is needed in the buffer pool, saving disk I/O. But larger log files also mean that recovery is slower in case of a crash.

  • innodb_log_files_in_group

    The number of log files in the log group. InnoDB writes to the files in a circular fashion. The default (and recommended) is 2.

  • innodb_log_group_home_dir

    The directory path to the InnoDB log files. If you do not specify any InnoDB log variables, the default is to create two 5MB files names ib_logfile0 and ib_logfile1 in the MySQL data directory.

  • innodb_max_dirty_pages_pct

    This is an integer in the range from 0 to 100. The default is 90. The main thread in InnoDB tries to write pages from the buffer pool so that the percentage of dirty (not yet written) pages will not exceed this value.

  • innodb_max_purge_lag

    This variable controls how to delay INSERT, UPDATE and DELETE operations when the purge operations are lagging (see Section 14.5.12, “Implementation of Multi-Versioning”). The default value of this variable is 0, meaning that there are no delays.

    The InnoDB transaction system maintains a list of transactions that have delete-marked index records by UPDATE or DELETE operations. Let the length of this list be purge_lag. When purge_lag exceeds innodb_max_purge_lag, each INSERT, UPDATE and DELETE operation is delayed by ((purge_lag/innodb_max_purge_lag)×10)–5 milliseconds. The delay is computed in the beginning of a purge batch, every ten seconds. The operations are not delayed if purge cannot run because of an old consistent read view that could see the rows to be purged.

    A typical setting for a problematic workload might be 1 million, assuming that our transactions are small, only 100 bytes in size, and we can allow 100MB of unpurged rows in our tables.

  • innodb_mirrored_log_groups

    The number of identical copies of log groups to keep for the database. Currently, this should be set to 1.

  • innodb_open_files

    This variable is relevant only if you use multiple tablespaces in InnoDB. It specifies the maximum number of .ibd files that InnoDB can keep open at one time. The minimum value is 10. The default is 300.

    The file descriptors used for .ibd files are for InnoDB only. They are independent of those specified by the --open-files-limit server option, and do not affect the operation of the table cache.

  • innodb_rollback_on_timeout

    In MySQL 5.1, InnoDB rolls back only the last statement on a transaction timeout. If this option is given, a transaction timeout causes InnoDB to abort and roll back the entire transaction (the same behavior as in MySQL 4.1). This variable was added in MySQL 5.1.15.

  • innodb_support_xa

    When set to ON or 1 (the default), this variable enables InnoDB support for two-phase commit in XA transactions. Enabling innodb_support_xa causes an extra disk flush for transaction preparation. If you don't care about using XA, you can disable this variable by setting it to OFF or 0 to reduce the number of disk flushes and get better InnoDB performance.

  • innodb_sync_spin_loops

    The number of times a thread waits for an InnoDB mutex to be freed before the thread is suspended.

  • innodb_table_locks

    If AUTOCOMMIT=0, InnoDB honors LOCK TABLES; MySQL does not return from LOCK TABLE .. WRITE until all other threads have released all their locks to the table. The default value of innodb_table_locks is 1, which means that LOCK TABLES causes InnoDB to lock a table internally if AUTOCOMMIT=0.

  • innodb_thread_concurrency

    InnoDB tries to keep the number of operating system threads concurrently inside InnoDB less than or equal to the limit given by this variable. If you have performance issues, and SHOW ENGINE INNODB STATUS reveals many threads waiting for semaphores, you may have thread “thrashing” and should try setting this variable lower or higher. If you have a computer with many processors and disks, you can try setting the value higher to make better use of your computer's resources. A recommended value is the sum of the number of processors and disks your system has.

    The range of this variable is 0 to 1000. A value of 20 or higher is interpreted as infinite concurrency. Infinite means that concurrency checking is disabled and the possibly considerable overhead of acquiring and releasing a mutex is avoided.

    The default value is 20 before MySQL 5.1.11, and 8 from 5.1.11 on.

  • innodb_thread_sleep_delay

    How long InnoDB threads sleep before joining the InnoDB queue, in microseconds. The default value is 10,000. A value of 0 disables sleep.

  • sync_binlog

    If the value of this variable is positive, the MySQL server synchronizes its binary log to disk (fdatasync()) after every sync_binlog writes to this binary log. Note that there is one write to the binary log per statement if in autocommit mode, and otherwise one write per transaction. The default value is 0 which does no synchronizing to disk. A value of 1 is the safest choice, because in the event of a crash you lose at most one statement/transaction from the binary log; however, it is also the slowest choice (unless the disk has a battery-backed cache, which makes synchronization very fast).

14.5.5. Creating the InnoDB Tablespace

Suppose that you have installed MySQL and have edited your option file so that it contains the necessary InnoDB configuration parameters. Before starting MySQL, you should verify that the directories you have specified for InnoDB data files and log files exist and that the MySQL server has access rights to those directories. InnoDB does not create directories, only files. Check also that you have enough disk space for the data and log files.

It is best to run the MySQL server mysqld from the command prompt when you first start the server with InnoDB enabled, not from the mysqld_safe wrapper or as a Windows service. When you run from a command prompt you see what mysqld prints and what is happening. On Unix, just invoke mysqld. On Windows, use the --console option.

When you start the MySQL server after initially configuring InnoDB in your option file, InnoDB creates your data files and log files, and prints something like this:

InnoDB: The first specified datafile /home/heikki/data/ibdata1
did not exist:
InnoDB: a new database to be created!
InnoDB: Setting file /home/heikki/data/ibdata1 size to 134217728
InnoDB: Database physically writes the file full: wait...
InnoDB: datafile /home/heikki/data/ibdata2 did not exist:
new to be created
InnoDB: Setting file /home/heikki/data/ibdata2 size to 262144000
InnoDB: Database physically writes the file full: wait...
InnoDB: Log file /home/heikki/data/logs/ib_logfile0 did not exist:
new to be created
InnoDB: Setting log file /home/heikki/data/logs/ib_logfile0 size
to 5242880
InnoDB: Log file /home/heikki/data/logs/ib_logfile1 did not exist:
new to be created
InnoDB: Setting log file /home/heikki/data/logs/ib_logfile1 size
to 5242880
InnoDB: Doublewrite buffer not found: creating new
InnoDB: Doublewrite buffer created
InnoDB: Creating foreign key constraint system tables
InnoDB: Foreign key constraint system tables created
InnoDB: Started
mysqld: ready for connections

At this point InnoDB has initialized its tablespace and log files. You can connect to the MySQL server with the usual MySQL client programs like mysql. When you shut down the MySQL server with mysqladmin shutdown, the output is like this:

010321 18:33:34  mysqld: Normal shutdown
010321 18:33:34  mysqld: Shutdown Complete
InnoDB: Starting shutdown...
InnoDB: Shutdown completed

You can look at the data file and log directories and you see the files created there. When MySQL is started again, the data files and log files have been created already, so the output is much briefer:

InnoDB: Started
mysqld: ready for connections

If you add the innodb_file_per_table option to my.cnf, InnoDB stores each table in its own .ibd file in the same MySQL database directory where the .frm file is created. See Section 14.5.3.1, “Using Per-Table Tablespaces”.

14.5.5.1. Dealing with InnoDB Initialization Problems

If InnoDB prints an operating system error during a file operation, usually the problem has one of the following causes:

  • You did not create the InnoDB data file directory or the InnoDB log directory.

  • mysqld does not have access rights to create files in those directories.

  • mysqld cannot read the proper my.cnf or my.ini option file, and consequently does not see the options that you specified.

  • The disk is full or a disk quota is exceeded.

  • You have created a subdirectory whose name is equal to a data file that you specified, so the name cannot be used as a filename.

  • There is a syntax error in the innodb_data_home_dir or innodb_data_file_path value.

If something goes wrong when InnoDB attempts to initialize its tablespace or its log files, you should delete all files created by InnoDB. This means all ibdata files and all ib_logfile files. In case you have already created some InnoDB tables, delete the corresponding .frm files for these tables (and any .ibd files if you are using multiple tablespaces) from the MySQL database directories as well. Then you can try the InnoDB database creation again. It is best to start the MySQL server from a command prompt so that you see what is happening.

14.5.6. Creating and Using InnoDB Tables

To create an InnoDB table, specify an ENGINE = InnoDB option in the CREATE TABLE statement:

CREATE TABLE customers (a INT, b CHAR (20), INDEX (a)) ENGINE=InnoDB;

The statement creates a table and an index on column a in the InnoDB tablespace that consists of the data files that you specified in my.cnf. In addition, MySQL creates a file customers.frm in the test directory under the MySQL database directory. Internally, InnoDB adds an entry for the table to its own data dictionary. The entry includes the database name. For example, if test is the database in which the customers table is created, the entry is for 'test/customers'. This means you can create a table of the same name customers in some other database, and the table names do not collide inside InnoDB.

You can query the amount of free space in the InnoDB tablespace by issuing a SHOW TABLE STATUS statement for any InnoDB table. The amount of free space in the tablespace appears in the Comment section in the output of SHOW TABLE STATUS. For example:

SHOW TABLE STATUS FROM test LIKE 'customers'

Note that the statistics SHOW displays for InnoDB tables are only approximate. They are used in SQL optimization. Table and index reserved sizes in bytes are accurate, though.

14.5.6.1. How to Use Transactions in InnoDB with Different APIs

By default, each client that connects to the MySQL server begins with autocommit mode enabled, which automatically commits every SQL statement as you execute it. To use multiple-statement transactions, you can switch autocommit off with the SQL statement SET AUTOCOMMIT = 0 and use COMMIT and ROLLBACK to commit or roll back your transaction. If you want to leave autocommit on, you can enclose your transactions within START TRANSACTION and either COMMIT or ROLLBACK. The following example shows two transactions. The first is committed; the second is rolled back.

shell> mysql test

mysql> CREATE TABLE CUSTOMER (A INT, B CHAR (20), INDEX (A))
    -> ENGINE=InnoDB;
Query OK, 0 rows affected (0.00 sec)
mysql> START TRANSACTION;
Query OK, 0 rows affected (0.00 sec)
mysql> INSERT INTO CUSTOMER VALUES (10, 'Heikki');
Query OK, 1 row affected (0.00 sec)
mysql> COMMIT;
Query OK, 0 rows affected (0.00 sec)
mysql> SET AUTOCOMMIT=0;
Query OK, 0 rows affected (0.00 sec)
mysql> INSERT INTO CUSTOMER VALUES (15, 'John');
Query OK, 1 row affected (0.00 sec)
mysql> ROLLBACK;
Query OK, 0 rows affected (0.00 sec)
mysql> SELECT * FROM CUSTOMER;
+------+--------+
| A    | B      |
+------+--------+
|   10 | Heikki |
+------+--------+
1 row in set (0.00 sec)
mysql>

In APIs such as PHP, Perl DBI, JDBC, ODBC, or the standard C call interface of MySQL, you can send transaction control statements such as COMMIT to the MySQL server as strings just like any other SQL statements such as SELECT or INSERT. Some APIs also offer separate special transaction commit and rollback functions or methods.

14.5.6.2. Converting MyISAM Tables to InnoDB

Important: Do not convert MySQL system tables in the mysql database (such as user or host) to the InnoDB type. This is an unsupported operation. The system tables must always be of the MyISAM type.

If you want all your (non-system) tables to be created as InnoDB tables, you can simply add the line default-storage-engine=innodb to the [mysqld] section of your server option file.

InnoDB does not have a special optimization for separate index creation the way the MyISAM storage engine does. Therefore, it does not pay to export and import the table and create indexes afterward. The fastest way to alter a table to InnoDB is to do the inserts directly to an InnoDB table. That is, use ALTER TABLE ... ENGINE=INNODB, or create an empty InnoDB table with identical definitions and insert the rows with INSERT INTO ... SELECT * FROM ....

If you have UNIQUE constraints on secondary keys, you can speed up a table import by turning off the uniqueness checks temporarily during the import operation:

SET UNIQUE_CHECKS=0;
... import operation ...
SET UNIQUE_CHECKS=1;

For big tables, this saves a lot of disk I/O because InnoDB can then use its insert buffer to write secondary index records as a batch. Be certain that the data contains no duplicate keys. UNIQUE_CHECKS allows but does not require storage engines to ignore duplicate keys.

To get better control over the insertion process, it might be good to insert big tables in pieces:

INSERT INTO newtable SELECT * FROM oldtable
   WHERE yourkey > something AND yourkey <= somethingelse;

After all records have been inserted, you can rename the tables.

During the conversion of big tables, you should increase the size of the InnoDB buffer pool to reduce disk I/O. Do not use more than 80% of the physical memory, though. You can also increase the sizes of the InnoDB log files.

Make sure that you do not fill up the tablespace: InnoDB tables require a lot more disk space than MyISAM tables. If an ALTER TABLE operation runs out of space, it starts a rollback, and that can take hours if it is disk-bound. For inserts, InnoDB uses the insert buffer to merge secondary index records to indexes in batches. That saves a lot of disk I/O. For rollback, no such mechanism is used, and the rollback can take 30 times longer than the insertion.

In the case of a runaway rollback, if you do not have valuable data in your database, it may be advisable to kill the database process rather than wait for millions of disk I/O operations to complete. For the complete procedure, see Section 14.5.8.1, “Forcing InnoDB Recovery”.

14.5.6.3. How AUTO_INCREMENT Columns Work in InnoDB

If you specify an AUTO_INCREMENT column for an InnoDB table, the table handle in the InnoDB data dictionary contains a special counter called the auto-increment counter that is used in assigning new values for the column. This counter is stored only in main memory, not on disk.

InnoDB uses the following algorithm to initialize the auto-increment counter for a table T that contains an AUTO_INCREMENT column named ai_col: After a server startup, for the first insert into a table T, InnoDB executes the equivalent of this statement:

SELECT MAX(ai_col) FROM T FOR UPDATE;

InnoDB increments by one the value retrieved by the statement and assigns it to the column and to the auto-increment counter for the table. If the table is empty, InnoDB uses the value 1. If a user invokes a SHOW TABLE STATUS statement that displays output for the table T and the auto-increment counter has not been initialized, InnoDB initializes but does not increment the value and stores it for use by later inserts. Note that this initialization uses a normal exclusive-locking read on the table and the lock lasts to the end of the transaction.

InnoDB follows the same procedure for initializing the auto-increment counter for a freshly created table.

After the auto-increment counter has been initialized, if a user does not explicitly specify a value for an AUTO_INCREMENT column, InnoDB increments the counter by one and assigns the new value to the column. If the user inserts a row that explicitly specifies the column value, and the value is bigger than the current counter value, the counter is set to the specified column value.

You may see gaps in the sequence of values assigned to the AUTO_INCREMENT column if you roll back transactions that have generated numbers using the counter.

If a user specifies NULL or 0 for the AUTO_INCREMENT column in an INSERT, InnoDB treats the row as if the value had not been specified and generates a new value for it.

The behavior of the auto-increment mechanism is not defined if a user assigns a negative value to the column or if the value becomes bigger than the maximum integer that can be stored in the specified integer type.

When accessing the auto-increment counter, InnoDB uses a special table-level AUTO-INC lock that it keeps to the end of the current SQL statement, not to the end of the transaction. The special lock release strategy was introduced to improve concurrency for inserts into a table containing an AUTO_INCREMENT column. Nevertheless, two transactions cannot have the AUTO-INC lock on the same table simultaneously, which can have a performance impact if the AUTO-INC lock is held for a long time. That might be the case for a statement such as INSERT INTO t1 ... SELECT ... FROM t2 that inserts all rows from one table into another.

InnoDB uses the in-memory auto-increment counter as long as the server runs. When the server is stopped and restarted, InnoDB reinitializes the counter for each table for the first INSERT to the table, as described earlier.

InnoDB supports the AUTO_INCREMENT = N table option in CREATE TABLE and ALTER TABLE statements, to set the initial counter value or alter the current counter value. The effect of this option is canceled by a server restart, for reasons discussed earlier in this section.

14.5.6.4. FOREIGN KEY Constraints

InnoDB also supports foreign key constraints. The syntax for a foreign key constraint definition in InnoDB looks like this:

[CONSTRAINT symbol] FOREIGN KEY [id] (index_col_name, ...)
    REFERENCES tbl_name (index_col_name, ...)
    [ON DELETE {RESTRICT | CASCADE | SET NULL | NO ACTION}]
    [ON UPDATE {RESTRICT | CASCADE | SET NULL | NO ACTION}]

Foreign keys definitions are subject to the following conditions:

  • Both tables must be InnoDB tables and they must not be TEMPORARY tables.

  • In the referencing table, there must be an index where the foreign key columns are listed as the first columns in the same order. Such an index is created on the referencing table automatically if it does not exist.

  • In the referenced table, there must be an index where the referenced columns are listed as the first columns in the same order.

  • Index prefixes on foreign key columns are not supported. One consequence of this is that BLOB and TEXT columns cannot be included in a foreign key, because indexes on those columns must always include a prefix length.

  • If the CONSTRAINT symbol clause is given, the symbol value must be unique in the database. If the clause is not given, InnoDB creates the name automatically.

InnoDB rejects any INSERT or UPDATE operation that attempts to create a foreign key value in a child table if there is no a matching candidate key value in the parent table. The action InnoDB takes for any UPDATE or DELETE operation that attempts to update or delete a candidate key value in the parent table that has some matching rows in the child table is dependent on the referential action specified using ON UPDATE and ON DELETE subclauses of the FOREIGN KEY clause. When the user attempts to delete or update a row from a parent table, and there are one or more matching rows in the child table, InnoDB supports five options regarding the action to be taken:

  • CASCADE: Delete or update the row from the parent table and automatically delete or update the matching rows in the child table. Both ON DELETE CASCADE and ON UPDATE CASCADE are supported. Between two tables, you should not define several ON UPDATE CASCADE clauses that act on the same column in the parent table or in the child table.

  • SET NULL: Delete or update the row from the parent table and set the foreign key column or columns in the child table to NULL. This is valid only if the foreign key columns do not have the NOT NULL qualifier specified. Both ON DELETE SET NULL and ON UPDATE SET NULL clauses are supported.

  • NO ACTION: In standard SQL, NO ACTION means no action in the sense that an attempt to delete or update a primary key value is not allowed to proceed if there is a related foreign key value in the referenced table. InnoDB rejects the delete or update operation for the parent table.

  • RESTRICT: Rejects the delete or update operation for the parent table. NO ACTION and RESTRICT are the same as omitting the ON DELETE or ON UPDATE clause. (Some database systems have deferred checks, and NO ACTION is a deferred check. In MySQL, foreign key constraints are checked immediately, so NO ACTION and RESTRICT are the same.)

  • SET DEFAULT: This action is recognized by the parser, but InnoDB rejects table definitions containing ON DELETE SET DEFAULT or ON UPDATE SET DEFAULT clauses.

Note that InnoDB supports foreign key references within a table. In these cases, “child table records” really refers to dependent records within the same table.

InnoDB requires indexes on foreign keys and referenced keys so that foreign key checks can be fast and not require a table scan. The index on the foreign key is created automatically. This is in contrast to some older versions, in which indexes had to be created explicitly or the creation of foreign key constraints would fail.

Corresponding columns in the foreign key and the referenced key must have similar internal data types inside InnoDB so that they can be compared without a type conversion. The size and sign of integer types must be the same. The length of string types need not be the same. If you specify a SET NULL action, make sure that you have not declared the columns in the child table as NOT NULL.

If MySQL reports an error number 1005 from a CREATE TABLE statement, and the error message refers to errno 150, table creation failed because a foreign key constraint was not correctly formed. Similarly, if an ALTER TABLE fails and it refers to errno 150, that means a foreign key definition would be incorrectly formed for the altered table. You can use SHOW ENGINE INNODB STATUS to display a detailed explanation of the most recent InnoDB foreign key error in the server.

Note: InnoDB does not check foreign key constraints on those foreign key or referenced key values that contain a NULL column.

Note: Currently, triggers are not activated by cascaded foreign key actions.

You cannot create a table with a column name that matches the name of an internal InnoDB column (including DB_ROW_ID, DB_TRX_ID, DB_ROLL_PTR and DB_MIX_ID). In versions of MySQL before 5.1.10 this would cause a crash, since 5.1.10 the server will report error 1005 and refers to errno -1 in the error message.

Deviation from SQL standards: If there are several rows in the parent table that have the same referenced key value, InnoDB acts in foreign key checks as if the other parent rows with the same key value do not exist. For example, if you have defined a RESTRICT type constraint, and there is a child row with several parent rows, InnoDB does not allow the deletion of any of those parent rows.

InnoDB performs cascading operations through a depth-first algorithm, based on records in the indexes corresponding to the foreign key constraints.

Deviation from SQL standards: A FOREIGN KEY constraint that references a non-UNIQUE key is not standard SQL. It is an InnoDB extension to standard SQL.

Deviation from SQL standards: If ON UPDATE CASCADE or ON UPDATE SET NULL recurses to update the same table it has previously updated during the cascade, it acts like RESTRICT. This means that you cannot use self-referential ON UPDATE CASCADE or ON UPDATE SET NULL operations. This is to prevent infinite loops resulting from cascaded updates. A self-referential ON DELETE SET NULL, on the other hand, is possible, as is a self-referential ON DELETE CASCADE. Cascading operations may not be nested more than 15 levels deep.

Deviation from SQL standards: Like MySQL in general, in an SQL statement that inserts, deletes, or updates many rows, InnoDB checks UNIQUE and FOREIGN KEY constraints row-by-row. According to the SQL standard, the default behavior should be deferred checking. That is, constraints are only checked after the entire SQL statement has been processed. Until InnoDB implements deferred constraint checking, some things will be impossible, such as deleting a record that refers to itself via a foreign key.

Here is a simple example that relates parent and child tables through a single-column foreign key:

CREATE TABLE parent (id INT NOT NULL,
                     PRIMARY KEY (id)
) ENGINE=INNODB;
CREATE TABLE child (id INT, parent_id INT,
                    INDEX par_ind (parent_id),
                    FOREIGN KEY (parent_id) REFERENCES parent(id)
                      ON DELETE CASCADE
) ENGINE=INNODB;

A more complex example in which a product_order table has foreign keys for two other tables. One foreign key references a two-column index in the product table. The other references a single-column index in the customer table:

CREATE TABLE product (category INT NOT NULL, id INT NOT NULL,
                      price DECIMAL,
                      PRIMARY KEY(category, id)) ENGINE=INNODB;
CREATE TABLE customer (id INT NOT NULL,
                       PRIMARY KEY (id)) ENGINE=INNODB;
CREATE TABLE product_order (no INT NOT NULL AUTO_INCREMENT,
                            product_category INT NOT NULL,
                            product_id INT NOT NULL,
                            customer_id INT NOT NULL,
                            PRIMARY KEY(no),
                            INDEX (product_category, product_id),
                            FOREIGN KEY (product_category, product_id)
                              REFERENCES product(category, id)
                              ON UPDATE CASCADE ON DELETE RESTRICT,
                            INDEX (customer_id),
                            FOREIGN KEY (customer_id)
                              REFERENCES customer(id)) ENGINE=INNODB;

InnoDB allows you to add a new foreign key constraint to a table by using ALTER TABLE:

ALTER TABLE tbl_name
    ADD [CONSTRAINT symbol] FOREIGN KEY [id] (index_col_name, ...)
    REFERENCES tbl_name (index_col_name, ...)
    [ON DELETE {RESTRICT | CASCADE | SET NULL | NO ACTION}]
    [ON UPDATE {RESTRICT | CASCADE | SET NULL | NO ACTION}]

Remember to create the required indexes first. You can also add a self-referential foreign key constraint to a table using ALTER TABLE.

InnoDB also supports the use of ALTER TABLE to drop foreign keys:

ALTER TABLE tbl_name DROP FOREIGN KEY fk_symbol;

If the FOREIGN KEY clause included a CONSTRAINT name when you created the foreign key, you can refer to that name to drop the foreign key. Otherwise, the fk_symbol value is internally generated by InnoDB when the foreign key is created. To find out the symbol value when you want to drop a foreign key, use the SHOW CREATE TABLE statement. For example:

mysql> SHOW CREATE TABLE ibtest11c\G
*************************** 1. row ***************************
       Table: ibtest11c
Create Table: CREATE TABLE `ibtest11c` (
  `A` int(11) NOT NULL auto_increment,
  `D` int(11) NOT NULL default '0',
  `B` varchar(200) NOT NULL default '',
  `C` varchar(175) default NULL,
  PRIMARY KEY  (`A`,`D`,`B`),
  KEY `B` (`B`,`C`),
  KEY `C` (`C`),
  CONSTRAINT `0_38775` FOREIGN KEY (`A`, `D`)
REFERENCES `ibtest11a` (`A`, `D`)
ON DELETE CASCADE ON UPDATE CASCADE,
  CONSTRAINT `0_38776` FOREIGN KEY (`B`, `C`)
REFERENCES `ibtest11a` (`B`, `C`)
ON DELETE CASCADE ON UPDATE CASCADE
) ENGINE=INNODB CHARSET=latin1
1 row in set (0.01 sec)

mysql> ALTER TABLE ibtest11c DROP FOREIGN KEY `0_38775`;

You cannot add a foreign key and drop a foreign key in separate clauses of a single ALTER TABLE statement. Separate statements are required.

The InnoDB parser allows table and column identifiers in a FOREIGN KEY ... REFERENCES ... clause to be quoted within backticks. (Alternatively, double quotes can be used if the ANSI_QUOTES SQL mode is enabled.) The InnoDB parser also takes into account the setting of the lower_case_table_names system variable.

InnoDB returns a table's foreign key definitions as part of the output of the SHOW CREATE TABLE statement:

SHOW CREATE TABLE tbl_name;

mysqldump also produces correct definitions of tables to the dump file, and does not forget about the foreign keys.

You can also display the foreign key constraints for a table like this:

SHOW TABLE STATUS FROM db_name LIKE 'tbl_name';

The foreign key constraints are listed in the Comment column of the output.

When performing foreign key checks, InnoDB sets shared row-level locks on child or parent records it has to look at. InnoDB checks foreign key constraints immediately; the check is not deferred to transaction commit.

To make it easier to reload dump files for tables that have foreign key relationships, mysqldump automatically includes a statement in the dump output to set FOREIGN_KEY_CHECKS to 0. This avoids problems with tables having to be reloaded in a particular order when the dump is reloaded. It is also possible to set this variable manually:

mysql> SET FOREIGN_KEY_CHECKS = 0;
mysql> SOURCE dump_file_name;
mysql> SET FOREIGN_KEY_CHECKS = 1;

This allows you to import the tables in any order if the dump file contains tables that are not correctly ordered for foreign keys. It also speeds up the import operation. Setting FOREIGN_KEY_CHECKS to 0 can also be useful for ignoring foreign key constraints during LOAD DATA and ALTER TABLE operations. However, even if FOREIGN_KEY_CHECKS=0, InnoDB does not allow the creation of a foreign key constraint where a column references a non-matching column type.

InnoDB does not allow you to drop a table that is referenced by a FOREIGN KEY constraint, unless you do SET FOREIGN_KEY_CHECKS=0. When you drop a table, the constraints that were defined in its create statement are also dropped.

If you re-create a table that was dropped, it must have a definition that conforms to the foreign key constraints referencing it. It must have the right column names and types, and it must have indexes on the referenced keys, as stated earlier. If these are not satisfied, MySQL returns error number 1005 and refers to errno 150 in the error message.

14.5.6.5. InnoDB and MySQL Replication

MySQL replication works for InnoDB tables as it does for MyISAM tables. It is also possible to use replication in a way where the storage engine on the slave is not the same as the original storage engine on the master. For example, you can replicate modifications to an InnoDB table on the master to a MyISAM table on the slave.

To set up a new slave for a master, you have to make a copy of the InnoDB tablespace and the log files, as well as the .frm files of the InnoDB tables, and move the copies to the slave. If the innodb_file_per_table variable is enabled, you must also copy the .ibd files as well. For the proper procedure to do this, see Section 14.5.8, “Backing Up and Recovering an InnoDB Database”.

If you can shut down the master or an existing slave, you can take a cold backup of the InnoDB tablespace and log files and use that to set up a slave. To make a new slave without taking down any server you can also use the non-free (commercial) InnoDB Hot Backup tool.

You cannot set up replication for InnoDB using the LOAD TABLE FROM MASTER statement, which works only for MyISAM tables. There are two possible workarounds:

  • Dump the table on the master and import the dump file into the slave.

  • Use ALTER TABLE tbl_name ENGINE=MyISAM on the master before setting up replication with LOAD TABLE tbl_name FROM MASTER, and then use ALTER TABLE to convert the master table back to InnoDB afterward. However, this should not be done for tables that have foreign key definitions because the definitions will be lost.

Transactions that fail on the master do not affect replication at all. MySQL replication is based on the binary log where MySQL writes SQL statements that modify data. A transaction that fails (for example, because of a foreign key violation, or because it is is rolled back) is not written to the binary log, so it is not sent to slaves. See Section 13.4.1, “START TRANSACTION, COMMIT, and ROLLBACK Syntax”.

14.5.7. Adding and Removing InnoDB Data and Log Files

This section describes what you can do when your InnoDB tablespace runs out of room or when you want to change the size of the log files.

The easiest way to increase the size of the InnoDB tablespace is to configure it from the beginning to be auto-extending. Specify the autoextend attribute for the last data file in the tablespace definition. Then InnoDB increases the size of that file automatically in 8MB increments when it runs out of space. The increment size can be changed by setting the value of the innodb_autoextend_increment system variable, which is measured in MB.

Alternatively, you can increase the size of your tablespace by adding another data file. To do this, you have to shut down the MySQL server, change the tablespace configuration to add a new data file to the end of innodb_data_file_path, and start the server again.

If your last data file was defined with the keyword autoextend, the procedure for reconfiguring the tablespace must take into account the size to which the last data file has grown. Obtain the size of the data file, round it down to the closest multiple of 1024 × 1024 bytes (= 1MB), and specify the rounded size explicitly in innodb_data_file_path. Then you can add another data file. Remember that only the last data file in the innodb_data_file_path can be specified as auto-extending.

As an example, assume that the tablespace has just one auto-extending data file ibdata1:

innodb_data_home_dir =
innodb_data_file_path = /ibdata/ibdata1:10M:autoextend

Suppose that this data file, over time, has grown to 988MB. Here is the configuration line after modifying the original data file to not be auto-extending and adding another auto-extending data file:

innodb_data_home_dir =
innodb_data_file_path = /ibdata/ibdata1:988M;/disk2/ibdata2:50M:autoextend

When you add a new file to the tablespace configuration, make sure that it does not exist. InnoDB will create and initialize the file when you restart the server.

Currently, you cannot remove a data file from the tablespace. To decrease the size of your tablespace, use this procedure:

  1. Use mysqldump to dump all your InnoDB tables.

  2. Stop the server.

  3. Remove all the existing tablespace files.

  4. Configure a new tablespace.

  5. Restart the server.

  6. Import the dump files.

If you want to change the number or the size of your InnoDB log files, use the following instructions. The procedure to use depends on the value of innodb_fast_shutdown:

  • If innodb_fast_shutdown is not set to 2: You must stop the MySQL server and make sure that it shuts down without errors (to ensure that there is no information for outstanding transactions in the logs). Then copy the old log files into a safe place just in case something went wrong in the shutdown and you need them to recover the tablespace. Delete the old log files from the log file directory, edit my.cnf to change the log file configuration, and start the MySQL server again. mysqld sees that no log files exist at startup and tells you that it is creating new ones.

  • If innodb_fast_shutdown is set to 2: You should shut down the server, set innodb_fast_shutdown to 1, and restart the server. The server should be allowed to recover. Then you should shut down the server again and follow the procedure described in the preceding item to change InnoDB log file size. Set innodb_fast_shutdown back to 2 and restart the server.

14.5.8. Backing Up and Recovering an InnoDB Database

The key to safe database management is making regular backups.

InnoDB Hot Backup is an online backup tool you can use to backup your InnoDB database while it is running. InnoDB Hot Backup does not require you to shut down your database and it does not set any locks or disturb your normal database processing. InnoDB Hot Backup is a non-free (commercial) add-on tool with an annual license fee of €390 per computer on which the MySQL server is run. See the InnoDB Hot Backup home page for detailed information and screenshots.

If you are able to shut down your MySQL server, you can make a binary backup that consists of all files used by InnoDB to manage its tables. Use the following procedure:

  1. Shut down your MySQL server and make sure that it shuts down without errors.

  2. Copy all your data files (ibdata files and .ibd files) into a safe place.

  3. Copy all your ib_logfile files to a safe place.

  4. Copy your my.cnf configuration file or files to a safe place.

  5. Copy all the .frm files for your InnoDB tables to a safe place.

Replication works with InnoDB tables, so you can use MySQL replication capabilities to keep a copy of your database at database sites requiring high availability.

In addition to making binary backups as just described, you should also regularly make dumps of your tables with mysqldump. The reason for this is that a binary file might be corrupted without you noticing it. Dumped tables are stored into text files that are human-readable, so spotting table corruption becomes easier. Also, because the format is simpler, the chance for serious data corruption is smaller. mysqldump also has a --single-transaction option that you can use to make a consistent snapshot without locking out other clients.

To be able to recover your InnoDB database to the present from the binary backup just described, you have to run your MySQL server with binary logging turned on. Then you can apply the binary log to the backup database to achieve point-in-time recovery:

mysqlbinlog yourhostname-bin.123 | mysql

To recover from a crash of your MySQL server, the only requirement is to restart it. InnoDB automatically checks the logs and performs a roll-forward of the database to the present. InnoDB automatically rolls back uncommitted transactions that were present at the time of the crash. During recovery, mysqld displays output something like this:

InnoDB: Database was not shut down normally.
InnoDB: Starting recovery from log files...
InnoDB: Starting log scan based on checkpoint at
InnoDB: log sequence number 0 13674004
InnoDB: Doing recovery: scanned up to log sequence number 0 13739520
InnoDB: Doing recovery: scanned up to log sequence number 0 13805056
InnoDB: Doing recovery: scanned up to log sequence number 0 13870592
InnoDB: Doing recovery: scanned up to log sequence number 0 13936128
...
InnoDB: Doing recovery: scanned up to log sequence number 0 20555264
InnoDB: Doing recovery: scanned up to log sequence number 0 20620800
InnoDB: Doing recovery: scanned up to log sequence number 0 20664692
InnoDB: 1 uncommitted transaction(s) which must be rolled back
InnoDB: Starting rollback of uncommitted transactions
InnoDB: Rolling back trx no 16745
InnoDB: Rolling back of trx no 16745 completed
InnoDB: Rollback of uncommitted transactions completed
InnoDB: Starting an apply batch of log records to the database...
InnoDB: Apply batch completed
InnoDB: Started
mysqld: ready for connections

If your database gets corrupted or your disk fails, you have to do the recovery from a backup. In the case of corruption, you should first find a backup that is not corrupted. After restoring the base backup, do the recovery from the binary log files using mysqlbinlog and mysql to restore the changes performed after the backup was made.

In some cases of database corruption it is enough just to dump, drop, and re-create one or a few corrupt tables. You can use the CHECK TABLE SQL statement to check whether a table is corrupt, although CHECK TABLE naturally cannot detect every possible kind of corruption. You can use innodb_tablespace_monitor to check the integrity of the file space management inside the tablespace files.

In some cases, apparent database page corruption is actually due to the operating system corrupting its own file cache, and the data on disk may be okay. It is best first to try restarting your computer. Doing so may eliminate errors that appeared to be database page corruption.

14.5.8.1. Forcing InnoDB Recovery

If there is database page corruption, you may want to dump your tables from the database with SELECT INTO OUTFILE. Usually, most of the data obtained in this way is intact. Even so, the corruption may cause SELECT * FROM tbl_name statements or InnoDB background operations to crash or assert, or even to cause InnoDB roll-forward recovery to crash. However, you can force the InnoDB storage engine to start up while preventing background operations from running, so that you are able to dump your tables. For example, you can add the following line to the [mysqld] section of your option file before restarting the server:

[mysqld]
innodb_force_recovery = 4

The allowable non-zero values for innodb_force_recovery follow. A larger number includes all precautions of smaller numbers. If you are able to dump your tables with an option value of at most 4, then you are relatively safe that only some data on corrupt individual pages is lost. A value of 6 is more drastic because database pages are left in an obsolete state, which in turn may introduce more corruption into B-trees and other database structures.

  • 1 (SRV_FORCE_IGNORE_CORRUPT)

    Let the server run even if it detects a corrupt page. Try to make SELECT * FROM tbl_name jump over corrupt index records and pages, which helps in dumping tables.

  • 2 (SRV_FORCE_NO_BACKGROUND)

    Prevent the main thread from running. If a crash would occur during the purge operation, this recovery value prevents it.

  • 3 (SRV_FORCE_NO_TRX_UNDO)

    Do not run transaction rollbacks after recovery.

  • 4 (SRV_FORCE_NO_IBUF_MERGE)

    Prevent also insert buffer merge operations. If they would cause a crash, do not do them. Do not calculate table statistics.

  • 5 (SRV_FORCE_NO_UNDO_LOG_SCAN)

    Do not look at undo logs when starting the database: InnoDB treats even incomplete transactions as committed.

  • 6 (SRV_FORCE_NO_LOG_REDO)

    Do not do the log roll-forward in connection with recovery.

You can SELECT from tables to dump them, or DROP or CREATE tables even if forced recovery is used. If you know that a given table is causing a crash on rollback, you can drop it. You can also use this to stop a runaway rollback caused by a failing mass import or ALTER TABLE. You can kill the mysqld process and set innodb_force_recovery to 3 to bring the database up without the rollback, then DROP the table that is causing the runaway rollback.

The database must not otherwise be used with any non-zero value of innodb_force_recovery. As a safety measure, InnoDB prevents users from performing INSERT, UPDATE, or DELETE operations when innodb_force_recovery is greater than 0.

14.5.8.2. Checkpoints

InnoDB implements a checkpoint mechanism known as “fuzzy” checkpointing. InnoDB flushes modified database pages from the buffer pool in small batches. There is no need to flush the buffer pool in one single batch, which would in practice stop processing of user SQL statements during the checkpointing process.

During crash recovery, InnoDB looks for a checkpoint label written to the log files. It knows that all modifications to the database before the label are present in the disk image of the database. Then InnoDB scans the log files forward from the checkpoint, applying the logged modifications to the database.

InnoDB writes to its log files on a rotating basis. All committed modifications that make the database pages in the buffer pool different from the images on disk must be available in the log files in case InnoDB has to do a recovery. This means that when InnoDB starts to reuse a log file, it has to make sure that the database page images on disk contain the modifications logged in the log file that InnoDB is going to reuse. In other words, InnoDB must create a checkpoint and this often involves flushing of modified database pages to disk.

The preceding description explains why making your log files very large may save disk I/O in checkpointing. It often makes sense to set the total size of the log files as big as the buffer pool or even bigger. The drawback of using large log files is that crash recovery can take longer because there is more logged information to apply to the database.

14.5.9. Moving an InnoDB Database to Another Machine

On Windows, InnoDB always stores database and table names internally in lowercase. To move databases in a binary format from Unix to Windows or from Windows to Unix, you should have all table and database names in lowercase. A convenient way to accomplish this is to add the following line to the [mysqld] section of your my.cnf or my.ini file before creating any databases or tables:

[mysqld]
lower_case_table_names=1

Like MyISAM data files, InnoDB data and log files are binary-compatible on all platforms having the same floating-point number format. You can move an InnoDB database simply by copying all the relevant files listed in Section 14.5.8, “Backing Up and Recovering an InnoDB Database”. If the floating-point formats differ but you have not used FLOAT or DOUBLE data types in your tables, then the procedure is the same: simply copy the relevant files. If the formats differ and your tables contain floating-point data, you must use mysqldump to dump your tables on one machine and then import the dump files on the other machine.

One way to increase performance is to switch off autocommit mode when importing data, assuming that the tablespace has enough space for the big rollback segment that the import transactions generate. Do the commit only after importing a whole table or a segment of a table.

14.5.10. InnoDB Transaction Model and Locking

In the InnoDB transaction model, the goal is to combine the best properties of a multi-versioning database with traditional two-phase locking. InnoDB does locking on the row level and runs queries as non-locking consistent reads by default, in the style of Oracle. The lock table in InnoDB is stored so space-efficiently that lock escalation is not needed: Typically several users are allowed to lock every row in the database, or any random subset of the rows, without InnoDB running out of memory.

14.5.10.1. InnoDB Lock Modes

InnoDB implements standard row-level locking where there are two types of locks:

  • A shared (S) lock allows a transaction to read a row (tuple).

  • An exclusive (X) lock allows a transaction to update or delete a row.

If transaction T1 holds a shared (S) lock on tuple t, then

  • A request from some distinct transaction T2 for an S lock on t can be granted immediately. As a result, both T1 and T2 hold an S lock on t.

  • A request from some distinct transaction T2 for an X lock on t cannot be granted immediately.

If a transaction T1 holds an exclusive (X) lock on tuple t, then a request from some distinct transaction T2 for a lock of either type on t cannot be granted immediately. Instead, transaction T2 has to wait for transaction T1 to release its lock on tuple t.

Additionally, InnoDB supports multiple granularity locking which allows coexistence of record locks and locks on entire tables. To make locking at multiple granularity levels practical, additional types of locks called intention locks are used. Intention locks are table locks in InnoDB. The idea behind intention locks is for a transaction to indicate which type of lock (shared or exclusive) it will require later for a row in that table. There are two types of intention locks used in InnoDB (assume that transaction T has requested a lock of the indicated type on table R):

  • Intention shared (IS): Transaction T intends to set S locks on individual rows in table R.

  • Intention exclusive (IX): Transaction T intends to set X locks on those rows.

The intention locking protocol is as follows:

  • Before a given transaction can acquire an S lock on a given row, it must first acquire an IS or stronger lock on the table containing that row.

  • Before a given transaction can acquire an X lock on a given row, it must first acquire an IX lock on the table containing that row.

These rules can be conveniently summarized by means of a lock type compatibility matrix:

 XIXSIS
XConflictConflictConflictConflict
IXConflictCompatibleConflictCompatible
SConflictConflictCompatibleCompatible
ISConflictCompatibleCompatibleCompatible

A lock is granted to a requesting transaction if it is compatible with existing locks. A lock is not granted to a requesting transaction if it conflicts with existing locks. A transaction waits until the conflicting existing lock is released. If a lock request conflicts with an existing lock and cannot be granted because it would cause deadlock, an error occurs.

Thus, intention locks do not block anything except full table requests (for example, LOCK TABLES ... WRITE). The main purpose of IX and IS locks is to show that someone is locking a row, or going to lock a row in the table.

The following example illustrates how an error can occur when a lock request would cause a deadlock. The example involves two clients, A and B.

First, client A creates a table containing one row, and then begins a transaction. Within the transaction, A obtains an S lock on the row by selecting it in share mode:

mysql> CREATE TABLE t (i INT) ENGINE = InnoDB;
Query OK, 0 rows affected (1.07 sec)

mysql> INSERT INTO t (i) VALUES(1);
Query OK, 1 row affected (0.09 sec)

mysql> START TRANSACTION;
Query OK, 0 rows affected (0.00 sec)

mysql> SELECT * FROM t WHERE i = 1 LOCK IN SHARE MODE;
+------+
| i    |
+------+
|    1 |
+------+
1 row in set (0.10 sec)

Next, client B begins a transaction and attempts to delete the row from the table:

mysql> START TRANSACTION;
Query OK, 0 rows affected (0.00 sec)

mysql> DELETE FROM t WHERE i = 1;

The delete operation requires an X lock. The lock cannot be granted because it is incompatible with the S lock that client A holds, so the request goes on the queue of lock requests for the row and client B blocks.

Finally, client A also attempts to delete the row from the table:

mysql> DELETE FROM t WHERE i = 1;
ERROR 1213 (40001): Deadlock found when trying to get lock;
try restarting transaction

Deadlock occurs here because client A needs an X lock to delete the row. However, that lock request cannot be granted because client B is already has a request for an X lock and is waiting for client A to release its S lock. Nor can the S lock held by A be upgraded to an X lock because of the prior request by B for an X lock. As a result, InnoDB generates an error for client A and releases its locks. At that point, the lock request for client B can be granted and B deletes the row from the table.

14.5.10.2. InnoDB and AUTOCOMMIT

In InnoDB, all user activity occurs inside a transaction. If the autocommit mode is enabled, each SQL statement forms a single transaction on its own. By default, MySQL starts new connections with autocommit enabled.

If the autocommit mode is switched off with SET AUTOCOMMIT = 0, then we can consider that a user always has a transaction open. An SQL COMMIT or ROLLBACK statement ends the current transaction and a new one starts. A COMMIT means that the changes made in the current transaction are made permanent and become visible to other users. A ROLLBACK statement, on the other hand, cancels all modifications made by the current transaction. Both statements release all InnoDB locks that were set during the current transaction.

If the connection has autocommit enabled, the user can still perform a multiple-statement transaction by starting it with an explicit START TRANSACTION or BEGIN statement and ending it with COMMIT or ROLLBACK.

14.5.10.3. InnoDB and TRANSACTION ISOLATION LEVEL

In terms of the SQL:1992 transaction isolation levels, the InnoDB default is REPEATABLE READ. InnoDB offers all four transaction isolation levels described by the SQL standard. You can set the default isolation level for all connections by using the --transaction-isolation option on the command line or in an option file. For example, you can set the option in the [mysqld] section of an option file like this:

[mysqld]
transaction-isolation = {READ-UNCOMMITTED | READ-COMMITTED
                         | REPEATABLE-READ | SERIALIZABLE}

A user can change the isolation level for a single session or for all new incoming connections with the SET TRANSACTION statement. Its syntax is as follows:

SET [SESSION | GLOBAL] TRANSACTION ISOLATION LEVEL
                       {READ UNCOMMITTED | READ COMMITTED
                        | REPEATABLE READ | SERIALIZABLE}

Note that there are hyphens in the level names for the --transaction-isolation option, but not for the SET TRANSACTION statement.

The default behavior is to set the isolation level for the next (not started) transaction. If you use the GLOBAL keyword, the statement sets the default transaction level globally for all new connections created from that point on (but not for existing connections). You need the SUPER privilege to do this. Using the SESSION keyword sets the default transaction level for all future transactions performed on the current connection.

Any client is free to change the session isolation level (even in the middle of a transaction), or the isolation level for the next transaction.

You can determine the global and session transaction isolation levels by checking the value of the tx_isolation system variable with these statements:

SELECT @@global.tx_isolation;
SELECT @@tx_isolation;

In row-level locking, InnoDB uses next-key locking. That means that besides index records, InnoDB can also lock the “gap” preceding an index record to block insertions by other users immediately before the index record. A next-key lock refers to a lock that locks an index record and the gap before it. A gap lock refers to a lock that only locks a gap before some index record.

A detailed description of each isolation level in InnoDB follows:

  • READ UNCOMMITTED

    SELECT statements are performed in a non-locking fashion, but a possible earlier version of a record might be used. Thus, using this isolation level, such reads are not consistent. This is also called a “dirty read.” Otherwise, this isolation level works like READ COMMITTED.

  • READ COMMITTED

    A somewhat Oracle-like isolation level. All SELECT ... FOR UPDATE and SELECT ... LOCK IN SHARE MODE statements lock only the index records, not the gaps before them, and thus allow the free insertion of new records next to locked records. UPDATE and DELETE statements using a unique index with a unique search condition lock only the index record found, not the gap before it. In range-type UPDATE and DELETE statements, InnoDB must set next-key or gap locks and block insertions by other users to the gaps covered by the range. This is necessary because “phantom rows” must be blocked for MySQL replication and recovery to work.

    Consistent reads behave as in Oracle: Each consistent read, even within the same transaction, sets and reads its own fresh snapshot. See Section 14.5.10.4, “Consistent Non-Locking Read”.

  • REPEATABLE READ

    This is the default isolation level of InnoDB. SELECT ... FOR UPDATE, SELECT ... LOCK IN SHARE MODE, UPDATE, and DELETE statements that use a unique index with a unique search condition lock only the index record found, not the gap before it. With other search conditions, these operations employ next-key locking, locking the index range scanned with next-key or gap locks, and block new insertions by other users.

    In consistent reads, there is an important difference from the READ COMMITTED isolation level: All consistent reads within the same transaction read the same snapshot established by the first read. This convention means that if you issue several plain SELECT statements within the same transaction, these SELECT statements are consistent also with respect to each other. See Section 14.5.10.4, “Consistent Non-Locking Read”.

  • SERIALIZABLE

    This level is like REPEATABLE READ, but InnoDB implicitly commits all plain SELECT statements to SELECT ... LOCK IN SHARE MODE.

14.5.10.4. Consistent Non-Locking Read

A consistent read means that InnoDB uses multi-versioning to present to a query a snapshot of the database at a point in time. The query see the changes made by those transactions that committed before that point of time, and no changes made by later or uncommitted transactions. The exception to this rule is that the query sees the changes made by earlier statements within the same transaction. Note that the exception to the rule causes the following anomaly: if you update some rows in a table, a SELECT will see the latest version of the updated rows, while it sees the old version of other rows. If other users simultaneously update the same table, the anomaly means that you may see the table in a state that never existed in the database.

If you are running with the default REPEATABLE READ isolation level, all consistent reads within the same transaction read the snapshot established by the first such read in that transaction. You can get a fresher snapshot for your queries by committing the current transaction and after that issuing new queries.

Consistent read is the default mode in which InnoDB processes SELECT statements in READ COMMITTED and REPEATABLE READ isolation levels. A consistent read does not set any locks on the tables it accesses, and therefore other users are free to modify those tables at the same time a consistent read is being performed on the table.

Note that consistent read does not work over DROP TABLE and over ALTER TABLE. Consistent read does not work over DROP TABLE because MySQL can't use a table that has been dropped and InnoDB destroys the table. Consistent read does not work over ALTER TABLE because ALTER TABLE works by making a temporary copy of the original table and deleting the original table when the temporary copy is built. When you reissue a consistent read within a transaction, rows in the new table are not visible because those rows did not exist when the transaction's snapshot was taken.

14.5.10.5. SELECT ... FOR UPDATE and SELECT ... LOCK IN SHARE MODE Locking Reads

In some circumstances, a consistent read is not convenient. For example, you might want to add a new row into your table child, and make sure that the child has a parent in table parent. The following example shows how to implement referential integrity in your application code.

Suppose that you use a consistent read to read the table parent and indeed see the parent of the child in the table. Can you safely add the child row to table child? No, because it may happen that meanwhile some other user deletes the parent row from the table parent without you being aware of it.

The solution is to perform the SELECT in a locking mode using LOCK IN SHARE MODE:

SELECT * FROM parent WHERE NAME = 'Jones' LOCK IN SHARE MODE;

Performing a read in share mode means that we read the latest available data, and set a shared mode lock on the rows we read. A shared mode lock prevents others from updating or deleting the row we have read. Also, if the latest data belongs to a yet uncommitted transaction of another client connection, we wait until that transaction commits. After we see that the preceding query returns the parent 'Jones', we can safely add the child record to the child table and commit our transaction.

Let us look at another example: We have an integer counter field in a table child_codes that we use to assign a unique identifier to each child added to table child. Obviously, using a consistent read or a shared mode read to read the present value of the counter is not a good idea because two users of the database may then see the same value for the counter, and a duplicate-key error occurs if two users attempt to add children with the same identifier to the table.

Here, LOCK IN SHARE MODE is not a good solution because if two users read the counter at the same time, at least one of them ends up in deadlock when attempting to update the counter.

In this case, there are two good ways to implement the reading and incrementing of the counter: (1) update the counter first by incrementing it by 1 and only after that read it, or (2) read the counter first with a lock mode FOR UPDATE, and increment after that. The latter approach can be implemented as follows:

SELECT counter_field FROM child_codes FOR UPDATE;
UPDATE child_codes SET counter_field = counter_field + 1;

A SELECT ... FOR UPDATE reads the latest available data, setting exclusive locks on each row it reads. Thus, it sets the same locks a searched SQL UPDATE would set on the rows.

The preceding description is merely an example of how SELECT ... FOR UPDATE works. In MySQL, the specific task of generating a unique identifier actually can be accomplished using only a single access to the table:

UPDATE child_codes SET counter_field = LAST_INSERT_ID(counter_field + 1);
SELECT LAST_INSERT_ID();

The SELECT statement merely retrieves the identifier information (specific to the current connection). It does not access any table.

Locks set by IN SHARE MODE and FOR UPDATE reads are released when the transaction is committed or rolled back.

14.5.10.6. Next-Key Locking: Avoiding the Phantom Problem

In row-level locking, InnoDB uses an algorithm called next-key locking. InnoDB performs the row-level locking in such a way that when it searches or scans an index of a table, it sets shared or exclusive locks on the index records it encounters. Thus, the row-level locks are actually index record locks.

The locks InnoDB sets on index records also affect the “gap” before that index record. If a user has a shared or exclusive lock on record R in an index, another user cannot insert a new index record immediately before R in the index order. This locking of gaps is done to prevent the so-called “phantom problem.” Suppose that you want to read and lock all children from the child table having an identifier value greater than 100, with the intention of updating some column in the selected rows later:

SELECT * FROM child WHERE id > 100 FOR UPDATE;

Suppose that there is an index on the id column. The query scans that index starting from the first record where id is bigger than 100. If the locks set on the index records would not lock out inserts made in the gaps, a new row might meanwhile be inserted to the table. If you execute the same SELECT within the same transaction, you would see a new row in the result set returned by the query. This is contrary to the isolation principle of transactions: A transaction should be able to run so that the data it has read does not change during the transaction. If we regard a set of rows as a data item, the new “phantom” child would violate this isolation principle.

When InnoDB scans an index, it can also lock the gap after the last record in the index. Just that happens in the previous example: The locks set by InnoDB prevent any insert to the table where id would be bigger than 100.

You can use next-key locking to implement a uniqueness check in your application: If you read your data in share mode and do not see a duplicate for a row you are going to insert, then you can safely insert your row and know that the next-key lock set on the successor of your row during the read prevents anyone meanwhile inserting a duplicate for your row. Thus, the next-key locking allows you to “lock” the non-existence of something in your table.

14.5.10.7. An Example of Consistent Read in InnoDB

Suppose that you are running in the default REPEATABLE READ isolation level. When you issue a consistent read (that is, an ordinary SELECT statement), InnoDB gives your transaction a timepoint according to which your query sees the database. If another transaction deletes a row and commits after your timepoint was assigned, you do not see the row as having been deleted. Inserts and updates are treated similarly.

You can advance your timepoint by committing your transaction and then doing another SELECT.

This is called multi-versioned concurrency control.

               User A                 User B

           SET AUTOCOMMIT=0;      SET AUTOCOMMIT=0;
time
|          SELECT * FROM t;
|          empty set
|                                 INSERT INTO t VALUES (1, 2);
|
v          SELECT * FROM t;
           empty set
                                  COMMIT;

           SELECT * FROM t;
           empty set

           COMMIT;

           SELECT * FROM t;
           ---------------------
           |    1    |    2    |
           ---------------------
           1 row in set

In this example, user A sees the row inserted by B only when B has committed the insert and A has committed as well, so that the timepoint is advanced past the commit of B.

If you want to see the “freshest” state of the database, you should use either the READ COMMITTED isolation level or a locking read:

SELECT * FROM t LOCK IN SHARE MODE;

14.5.10.8. Locks Set by Different SQL Statements in InnoDB

A locking read, an UPDATE, or a DELETE generally set record locks on every index record that is scanned in the processing of the SQL statement. It does not matter if there are WHERE conditions in the statement that would exclude the row. InnoDB does not remember the exact WHERE condition, but only knows which index ranges were scanned. The record locks are normally next-key locks that also block inserts to the “gap” immediately before the record.

If the locks to be set are exclusive, InnoDB always retrieves also the clustered index record and sets a lock on it.

If you do not have indexes suitable for your statement and MySQL has to scan the whole table to process the statement, every row of the table becomes locked, which in turn blocks all inserts by other users to the table. It is important to create good indexes so that your queries do not unnecessarily need to scan many rows.

InnoDB sets specific types of locks as follows:

  • SELECT ... FROM is a consistent read, reading a snapshot of the database and setting no locks unless the transaction isolation level is set to SERIALIZABLE. For SERIALIZABLE level, this sets shared next-key locks on the index records it encounters.

  • SELECT ... FROM ... LOCK IN SHARE MODE sets shared next-key locks on all index records the read encounters.

  • SELECT ... FROM ... FOR UPDATE sets exclusive next-key locks on all index records the read encounters.

  • INSERT INTO ... VALUES (...) sets an exclusive lock on the inserted row. Note that this lock is not a next-key lock and does not prevent other users from inserting to the gap before the inserted row. If a duplicate-key error occurs, a shared lock on the duplicate index record is set.

  • While initializing a previously specified AUTO_INCREMENT column on a table, InnoDB sets an exclusive lock on the end of the index associated with the AUTO_INCREMENT column. In accessing the auto-increment counter, InnoDB uses a specific table lock mode AUTO-INC where the lock lasts only to the end of the current SQL statement, not to the end of the entire transaction. Note that other clients cannot insert into the table while the AUTO-INC table lock is held; see Section 14.5.10.2, “InnoDB and AUTOCOMMIT.

    InnoDB fetches the value of a previously initialized AUTO_INCREMENT column without setting any locks.

  • INSERT INTO T SELECT ... FROM S WHERE ... sets an exclusive (non-next-key) lock on each row inserted into T. InnoDB sets shared next-key locks locks on S, unless innodb_locks_unsafe_for_binlog is enabled, in which case it does the search on S as a consistent read. InnoDB has to set locks in the latter case: In roll-forward recovery from a backup, every SQL statement has to be executed in exactly the same way it was done originally.

  • CREATE TABLE ... SELECT ... performs the SELECT as a consistent read or with shared locks, as in the previous item.

  • REPLACE is done like an insert if there is no collision on a unique key. Otherwise, an exclusive next-key lock is placed on the row that has to be updated.

  • UPDATE ... WHERE ... sets an exclusive next-key lock on every record the search encounters.

  • DELETE FROM ... WHERE ... sets an exclusive next-key lock on every record the search encounters.

  • If a FOREIGN KEY constraint is defined on a table, any insert, update, or delete that requires the constraint condition to be checked sets shared record-level locks on the records that it looks at to check the constraint. InnoDB also sets these locks in the case where the constraint fails.

  • LOCK TABLES sets table locks, but it is the higher MySQL layer above the InnoDB layer that sets these locks. InnoDB is aware of table locks if innodb_table_locks=1 (the default) and AUTOCOMMIT=0, and the MySQL layer above InnoDB knows about row-level locks. Otherwise, InnoDB's automatic deadlock detection cannot detect deadlocks where such table locks are involved. Also, because the higher MySQL layer does not know about row-level locks, it is possible to get a table lock on a table where another user currently has row-level locks. However, this does not endanger transaction integrity, as discussed in Section 14.5.10.10, “Deadlock Detection and Rollback”. See also Section 14.5.16, “Restrictions on InnoDB Tables”.

14.5.10.9. Implicit Transaction Commit and Rollback

By default, MySQL begins each client connection with autocommit mode enabled. When autocommit is enabled, MySQL does a commit after each SQL statement if that statement did not return an error. If an SQL statement returns an error, the commit or rollback behavior depends on the error. See Section 14.5.15, “InnoDB Error Handling”.

If you have the autocommit mode off and close a connection without explicitly committing the final transaction, MySQL rolls back that transaction.

Each of the following statements (and any synonyms for them) implicitly end a transaction, as if you had done a COMMIT before executing the statement:

  • ALTER FUNCTION, ALTER PROCEDURE, ALTER TABLE, BEGIN, CREATE DATABASE, CREATE FUNCTION, CREATE INDEX, CREATE PROCEDURE, CREATE TABLE, DROP DATABASE, DROP FUNCTION, DROP INDEX, DROP PROCEDURE, DROP TABLE, LOCK TABLES, RENAME TABLE, SET AUTOCOMMIT=1, START TRANSACTION, TRUNCATE, UNLOCK TABLES.

  • UNLOCK TABLES commits a transaction only if any tables are currently locked.

  • The CREATE TABLE statement in InnoDB is processed as a single transaction. This means that a ROLLBACK from the user does not undo CREATE TABLE statements the user made during that transaction.

  • CREATE TABLE and DROP TABLE do not commit a transaction if the TEMPORARY keyword is used. (This does not apply to other operations on temporary tables such as CREATE INDEX, which do cause a commit.)

  • In MySQL 5.1.11 and earlier, LOAD DATA INFILE caused an implicit commit for all storage engines. Beginning with MySQL 5.1.12, it causes an implicit commit only for tables using the NDB storage engine. For more information, see Bug#11151.

Transactions cannot be nested. This is a consequence of the implicit COMMIT performed for any current transaction when you issue a START TRANSACTION statement or one of its synonyms.

Statements that cause implicit cannot be used in an XA transaction while the transaction is in an ACTIVE state.

14.5.10.10. Deadlock Detection and Rollback

InnoDB automatically detects a deadlock of transactions and rolls back a transaction or transactions to break the deadlock. InnoDB tries to pick small transactions to roll back, where the size of a transaction is determined by the number of rows inserted, updated, or deleted.

InnoDB is aware of table locks if innodb_table_locks=1 (the default) and AUTOCOMMIT=0, and the MySQL layer above it knows about row-level locks. Otherwise, InnoDB cannot detect deadlocks where a table lock set by a MySQL LOCK TABLES statement or a lock set by a storage engine other than InnoDB is involved. You must resolve these situations by setting the value of the innodb_lock_wait_timeout system variable.

When InnoDB performs a complete rollback of a transaction, all locks set by the transaction are released. However, if just a single SQL statement is rolled back as a result of an error, some of the locks set by the statement may be preserved. This happens because InnoDB stores row locks in a format such that it cannot know afterward which lock was set by which statement.

14.5.10.11. How to Cope with Deadlocks

Deadlocks are a classic problem in transactional databases, but they are not dangerous unless they are so frequent that you cannot run certain transactions at all. Normally, you must write your applications so that they are always prepared to re-issue a transaction if it gets rolled back because of a deadlock.

InnoDB uses automatic row-level locking. You can get deadlocks even in the case of transactions that just insert or delete a single row. That is because these operations are not really “atomic”; they automatically set locks on the (possibly several) index records of the row inserted or deleted.

You can cope with deadlocks and reduce the likelihood of their occurrence with the following techniques:

  • Use SHOW ENGINE INNODB STATUS to determine the cause of the latest deadlock. That can help you to tune your application to avoid deadlocks.

  • Always be prepared to re-issue a transaction if it fails due to deadlock. Deadlocks are not dangerous. Just try again.

  • Commit your transactions often. Small transactions are less prone to collision.

  • If you are using locking reads (SELECT ... FOR UPDATE or ... LOCK IN SHARE MODE), try using a lower isolation level such as READ COMMITTED.

  • Access your tables and rows in a fixed order. Then transactions form well-defined queues and do not deadlock.

  • Add well-chosen indexes to your tables. Then your queries need to scan fewer index records and consequently set fewer locks. Use EXPLAIN SELECT to determine which indexes the MySQL server regards as the most appropriate for your queries.

  • Use less locking. If you can afford to allow a SELECT to return data from an old snapshot, do not add the clause FOR UPDATE or LOCK IN SHARE MODE to it. Using the READ COMMITTED isolation level is good here, because each consistent read within the same transaction reads from its own fresh snapshot.

  • If nothing else helps, serialize your transactions with table-level locks. The correct way to use LOCK TABLES with transactional tables, such as InnoDB tables, is to set AUTOCOMMIT = 0 and not to call UNLOCK TABLES until after you commit the transaction explicitly. For example, if you need to write to table t1 and read from table t2, you can do this:

    SET AUTOCOMMIT=0;
    LOCK TABLES t1 WRITE, t2 READ, ...;
    ... do something with tables t1 and t2 here ...
    COMMIT;
    UNLOCK TABLES;
    

    Table-level locks make your transactions queue nicely, and deadlocks are avoided.

  • Another way to serialize transactions is to create an auxiliary “semaphore” table that contains just a single row. Have each transaction update that row before accessing other tables. In that way, all transactions happen in a serial fashion. Note that the InnoDB instant deadlock detection algorithm also works in this case, because the serializing lock is a row-level lock. With MySQL table-level locks, the timeout method must be used to resolve deadlocks.

  • In applications that use the LOCK TABLES command, MySQL does not set InnoDB table locks if AUTOCOMMIT=1.

14.5.11. InnoDB Performance Tuning Tips

  • In InnoDB, having a long PRIMARY KEY wastes a lot of disk space because its value must be stored with every secondary index record. (See Section 14.5.13, “InnoDB Table and Index Structures”.) Create an AUTO_INCREMENT column as the primary key if your primary key is long.

  • If the Unix top tool or the Windows Task Manager shows that the CPU usage percentage with your workload is less than 70%, your workload is probably disk-bound. Maybe you are making too many transaction commits, or the buffer pool is too small. Making the buffer pool bigger can help, but do not set it equal to more than 80% of physical memory.

  • Wrap several modifications into one transaction. InnoDB must flush the log to disk at each transaction commit if that transaction made modifications to the database. The rotation speed of a disk is typically at most 167 revolutions/second, which constrains the number of commits to the same 167th of a second if the disk does not “fool” the operating system.

  • If you can afford the loss of some of the latest committed transactions if a crash occurs, you can set the innodb_flush_log_at_trx_commit parameter to 0. InnoDB tries to flush the log once per second anyway, although the flush is not guaranteed.

  • Make your log files big, even as big as the buffer pool. When InnoDB has written the log files full, it has to write the modified contents of the buffer pool to disk in a checkpoint. Small log files cause many unnecessary disk writes. The drawback of big log files is that the recovery time is longer.

  • Make the log buffer quite large as well (on the order of 8MB).

  • Use the VARCHAR data type instead of CHAR if you are storing variable-length strings or if the column may contain many NULL values. A CHAR(N) column always takes N characters to store data, even if the string is shorter or its value is NULL. Smaller tables fit better in the buffer pool and reduce disk I/O.

    When using row_format=compact (the default InnoDB record format in MySQL 5.1) and variable-length character sets, such as utf8 or sjis, CHAR(N) will occupy a variable amount of space, at least N bytes.

  • In some versions of GNU/Linux and Unix, flushing files to disk with the Unix fsync() call (which InnoDB uses by default) and other similar methods is surprisingly slow. If you are dissatisfied with database write performance, you might try setting the innodb_flush_method parameter to O_DSYNC. Although O_DSYNC seems to be slower on most systems, yours might not be one of them.

  • When using the InnoDB storage engine on Solaris 10 for x86_64 architecture (AMD Opteron), it is important to mount any filesystems used for storing InnoDB-related files using the forcedirectio option. (The default on Solaris 10/x86_64 is not to use this option.) Failure to use forcedirectio causes a serious degradation of InnoDB's speed and performance on this platform.

    When using the InnoDB storage engine with a large innodb_buffer_pool_size value on any release of Solaris 2.6 and up and any platform (sparc/x86/x64/amd64), a significant performance gain can be achieved by placing InnoDB data files and log files on raw devices or on a separate direct I/O UFS filesystem (using mount option forcedirectio; see mount_ufs(1M)). Users of the Veritas filesystem VxFS should use the mount option convosync=direct.

    Other MySQL data files, such as those for MyISAM tables, should not be placed on a direct I/O filesystem. Executables or libraries must not be placed on a direct I/O filesystem.

  • When importing data into InnoDB, make sure that MySQL does not have autocommit mode enabled because that requires a log flush to disk for every insert. To disable autocommit during your import operation, surround it with SET AUTOCOMMIT and COMMIT statements:

    SET AUTOCOMMIT=0;
    ... SQL import statements ...
    COMMIT;
    

    If you use the mysqldump option --opt, you get dump files that are fast to import into an InnoDB table, even without wrapping them with the SET AUTOCOMMIT and COMMIT statements.

  • Beware of big rollbacks of mass inserts: InnoDB uses the insert buffer to save disk I/O in inserts, but no such mechanism is used in a corresponding rollback. A disk-bound rollback can take 30 times as long to perform as the corresponding insert. Killing the database process does not help because the rollback starts again on server startup. The only way to get rid of a runaway rollback is to increase the buffer pool so that the rollback becomes CPU-bound and runs fast, or to use a special procedure. See Section 14.5.8.1, “Forcing InnoDB Recovery”.

  • Beware also of other big disk-bound operations. Use DROP TABLE and CREATE TABLE to empty a table, not DELETE FROM tbl_name.

  • Use the multiple-row INSERT syntax to reduce communication overhead between the client and the server if you need to insert many rows:

    INSERT INTO yourtable VALUES (1,2), (5,5), ...;
    

    This tip is valid for inserts into any table, not just InnoDB tables.

  • If you have UNIQUE constraints on secondary keys, you can speed up table imports by temporarily turning off the uniqueness checks during the import session:

    SET UNIQUE_CHECKS=0;
    ... import operation ...
    SET UNIQUE_CHECKS=1;
    

    For big tables, this saves a lot of disk I/O because InnoDB can use its insert buffer to write secondary index records in a batch. Be certain that the data contains no duplicate keys. UNIQUE_CHECKS allows but does not require storage engines to ignore duplicate keys.

  • If you have FOREIGN KEY constraints in your tables, you can speed up table imports by turning the foreign key checks off for the duration of the import session:

    SET FOREIGN_KEY_CHECKS=0;
    ... import operation ...
    SET FOREIGN_KEY_CHECKS=1;
    

    For big tables, this can save a lot of disk I/O.

  • If you often have recurring queries for tables that are not updated frequently, use the query cache:

    [mysqld]
    query_cache_type = ON
    query_cache_size = 10M
    
  • Unlike MyISAM, InnoDB does not store an index cardinality value in its tables. Instead, InnoDB computes a cardinality for a table the first time it accesses it after startup. With a large number of tables, this might take significant time. It is the initial table open operation that is important, so to “warm up” a table for later use, you might want to use it immediately after start up by issuing a statement such as SELECT 1 FROM tbl_name LIMIT 1.

14.5.11.1. SHOW ENGINE INNODB STATUS and the InnoDB Monitors

InnoDB includes InnoDB Monitors that print information about the InnoDB internal state. You can use the SHOW ENGINE INNODB STATUS SQL statement at any time to fetch the output of the standard InnoDB Monitor to your SQL client. This information is useful in performance tuning. (If you are using the mysql interactive SQL client, the output is more readable if you replace the usual semicolon statement terminator with \G.) For a discussion of InnoDB lock modes, see Section 14.5.10.1, “InnoDB Lock Modes”.

mysql> SHOW ENGINE INNODB STATUS\G

Another way to use InnoDB Monitors is to let them periodically write data to the standard output of the mysqld server. In this case, no output is sent to clients. When switched on, InnoDB Monitors print data about every 15 seconds. Server output usually is directed to the .err log in the MySQL data directory. This data is useful in performance tuning. On Windows, you must start the server from a command prompt in a console window with the --console option if you want to direct the output to the window rather than to the error log.

Monitor output includes the following types of information:

  • Table and record locks held by each active transaction

  • Lock waits of a transactions

  • Semaphore waits of threads

  • Pending file I/O requests

  • Buffer pool statistics

  • Purge and insert buffer merge activity of the main InnoDB thread

To cause the standard InnoDB Monitor to write to the standard output of mysqld, use the following SQL statement:

CREATE TABLE innodb_monitor (a INT) ENGINE=INNODB;

The monitor can be stopped by issuing the following statement:

DROP TABLE innodb_monitor;

The CREATE TABLE syntax is just a way to pass a command to the InnoDB engine through MySQL's SQL parser: The only things that matter are the table name innodb_monitor and that it be an InnoDB table. The structure of the table is not relevant at all for the InnoDB Monitor. If you shut down the server, the monitor does not restart automatically when you restart the server. You must drop the monitor table and issue a new CREATE TABLE statement to start the monitor. (This syntax may change in a future release.)

You can use innodb_lock_monitor in a similar fashion. This is the same as innodb_monitor, except that it also provides a great deal of lock information. A separate innodb_tablespace_monitor prints a list of created file segments existing in the tablespace and validates the tablespace allocation data structures. In addition, there is innodb_table_monitor with which you can print the contents of the InnoDB internal data dictionary.

A sample of InnoDB Monitor output:

mysql> SHOW ENGINE INNODB STATUS\G
*************************** 1. row ***************************
Status:
=====================================
030709 13:00:59 INNODB MONITOR OUTPUT
=====================================
Per second averages calculated from the last 18 seconds
----------
SEMAPHORES
----------
OS WAIT ARRAY INFO: reservation count 413452, signal count 378357
--Thread 32782 has waited at btr0sea.c line 1477 for 0.00 seconds the
semaphore: X-lock on RW-latch at 41a28668 created in file btr0sea.c line 135
a writer (thread id 32782) has reserved it in mode wait exclusive
number of readers 1, waiters flag 1
Last time read locked in file btr0sea.c line 731
Last time write locked in file btr0sea.c line 1347
Mutex spin waits 0, rounds 0, OS waits 0
RW-shared spins 108462, OS waits 37964; RW-excl spins 681824, OS waits
375485
------------------------
LATEST FOREIGN KEY ERROR
------------------------
030709 13:00:59 Transaction:
TRANSACTION 0 290328284, ACTIVE 0 sec, process no 3195, OS thread id 34831
inserting
15 lock struct(s), heap size 2496, undo log entries 9
MySQL thread id 25, query id 4668733 localhost heikki update
insert into ibtest11a (D, B, C) values (5, 'khDk' ,'khDk')
Foreign key constraint fails for table test/ibtest11a:
,
  CONSTRAINT `0_219242` FOREIGN KEY (`A`, `D`) REFERENCES `ibtest11b` (`A`,
  `D`) ON DELETE CASCADE ON UPDATE CASCADE
Trying to add in child table, in index PRIMARY tuple:
 0: len 4; hex 80000101; asc ....;; 1: len 4; hex 80000005; asc ....;; 2:
 len 4; hex 6b68446b; asc khDk;; 3: len 6; hex 0000114e0edc; asc ...N..;; 4:
 len 7; hex 00000000c3e0a7; asc .......;; 5: len 4; hex 6b68446b; asc khDk;;
But in parent table test/ibtest11b, in index PRIMARY,
the closest match we can find is record:
RECORD: info bits 0 0: len 4; hex 8000015b; asc ...[;; 1: len 4; hex
80000005; asc ....;; 2: len 3; hex 6b6864; asc khd;; 3: len 6; hex
0000111ef3eb; asc ......;; 4: len 7; hex 800001001e0084; asc .......;; 5:
len 3; hex 6b6864; asc khd;;
------------------------
LATEST DETECTED DEADLOCK
------------------------
030709 12:59:58
*** (1) TRANSACTION:
TRANSACTION 0 290252780, ACTIVE 1 sec, process no 3185, OS thread id 30733
inserting
LOCK WAIT 3 lock struct(s), heap size 320, undo log entries 146
MySQL thread id 21, query id 4553379 localhost heikki update
INSERT INTO alex1 VALUES(86, 86, 794,'aA35818','bb','c79166','d4766t',
'e187358f','g84586','h794',date_format('2001-04-03 12:54:22','%Y-%m-%d
%H:%i'),7
*** (1) WAITING FOR THIS LOCK TO BE GRANTED:
RECORD LOCKS space id 0 page no 48310 n bits 568 table test/alex1 index
symbole trx id 0 290252780 lock mode S waiting
Record lock, heap no 324 RECORD: info bits 0 0: len 7; hex 61613335383138;
asc aa35818;; 1:
*** (2) TRANSACTION:
TRANSACTION 0 290251546, ACTIVE 2 sec, process no 3190, OS thread id 32782
inserting
130 lock struct(s), heap size 11584, undo log entries 437
MySQL thread id 23, query id 4554396 localhost heikki update
REPLACE INTO alex1 VALUES(NULL, 32, NULL,'aa3572','','c3572','d6012t','',
NULL,'h396', NULL, NULL, 7.31,7.31,7.31,200)
*** (2) HOLDS THE LOCK(S):
RECORD LOCKS space id 0 page no 48310 n bits 568 table test/alex1 index
symbole trx id 0 290251546 lock_mode X locks rec but not gap
Record lock, heap no 324 RECORD: info bits 0 0: len 7; hex 61613335383138;
asc aa35818;; 1:
*** (2) WAITING FOR THIS LOCK TO BE GRANTED:
RECORD LOCKS space id 0 page no 48310 n bits 568 table test/alex1 index
symbole trx id 0 290251546 lock_mode X locks gap before rec insert intention
waiting
Record lock, heap no 82 RECORD: info bits 0 0: len 7; hex 61613335373230;
asc aa35720;; 1:
*** WE ROLL BACK TRANSACTION (1)
------------
TRANSACTIONS
------------
Trx id counter 0 290328385
Purge done for trx's n:o < 0 290315608 undo n:o < 0 17
Total number of lock structs in row lock hash table 70
LIST OF TRANSACTIONS FOR EACH SESSION:
---TRANSACTION 0 0, not started, process no 3491, OS thread id 42002
MySQL thread id 32, query id 4668737 localhost heikki
show innodb status
---TRANSACTION 0 290328384, ACTIVE 0 sec, process no 3205, OS thread id
38929 inserting
1 lock struct(s), heap size 320
MySQL thread id 29, query id 4668736 localhost heikki update
insert into speedc values (1519229,1, 'hgjhjgghggjgjgjgjgjggjgjgjgjgjgggjgjg
jlhhgghggggghhjhghgggggghjhghghghghghhhhghghghjhhjghjghjkghjghjghjghjfhjfh
---TRANSACTION 0 290328383, ACTIVE 0 sec, process no 3180, OS thread id
28684 committing
1 lock struct(s), heap size 320, undo log entries 1
MySQL thread id 19, query id 4668734 localhost heikki update
insert into speedcm values (1603393,1, 'hgjhjgghggjgjgjgjgjggjgjgjgjgjgggjgj
gjlhhgghggggghhjhghgggggghjhghghghghghhhhghghghjhhjghjghjkghjghjghjghjfhjf
---TRANSACTION 0 290328327, ACTIVE 0 sec, process no 3200, OS thread id
36880 starting index read
LOCK WAIT 2 lock struct(s), heap size 320
MySQL thread id 27, query id 4668644 localhost heikki Searching rows for
update
update ibtest11a set B = 'kHdkkkk' where A = 89572
------- TRX HAS BEEN WAITING 0 SEC FOR THIS LOCK TO BE GRANTED:
RECORD LOCKS space id 0 page no 65556 n bits 232 table test/ibtest11a index
PRIMARY trx id 0 290328327 lock_mode X waiting
Record lock, heap no 1 RECORD: info bits 0 0: len 9; hex 73757072656d756d00;
asc supremum.;;
------------------
---TRANSACTION 0 290328284, ACTIVE 0 sec, process no 3195, OS thread id
34831 rollback of SQL statement
ROLLING BACK 14 lock struct(s), heap size 2496, undo log entries 9
MySQL thread id 25, query id 4668733 localhost heikki update
insert into ibtest11a (D, B, C) values (5, 'khDk' ,'khDk')
---TRANSACTION 0 290327208, ACTIVE 1 sec, process no 3190, OS thread id
32782
58 lock struct(s), heap size 5504, undo log entries 159
MySQL thread id 23, query id 4668732 localhost heikki update
REPLACE INTO alex1 VALUES(86, 46, 538,'aa95666','bb','c95666','d9486t',
'e200498f','g86814','h538',date_format('2001-04-03 12:54:22','%Y-%m-%d
%H:%i'),
---TRANSACTION 0 290323325, ACTIVE 3 sec, process no 3185, OS thread id
30733 inserting
4 lock struct(s), heap size 1024, undo log entries 165
MySQL thread id 21, query id 4668735 localhost heikki update
INSERT INTO alex1 VALUES(NULL, 49, NULL,'aa42837','','c56319','d1719t','',
NULL,'h321', NULL, NULL, 7.31,7.31,7.31,200)
--------
FILE I/O
--------
I/O thread 0 state: waiting for i/o request (insert buffer thread)
I/O thread 1 state: waiting for i/o request (log thread)
I/O thread 2 state: waiting for i/o request (read thread)
I/O thread 3 state: waiting for i/o request (write thread)
Pending normal aio reads: 0, aio writes: 0,
 ibuf aio reads: 0, log i/o's: 0, sync i/o's: 0
Pending flushes (fsync) log: 0; buffer pool: 0
151671 OS file reads, 94747 OS file writes, 8750 OS fsyncs
25.44 reads/s, 18494 avg bytes/read, 17.55 writes/s, 2.33 fsyncs/s
-------------------------------------
INSERT BUFFER AND ADAPTIVE HASH INDEX
-------------------------------------
Ibuf for space 0: size 1, free list len 19, seg size 21,
85004 inserts, 85004 merged recs, 26669 merges
Hash table size 207619, used cells 14461, node heap has 16 buffer(s)
1877.67 hash searches/s, 5121.10 non-hash searches/s
---
LOG
---
Log sequence number 18 1212842764
Log flushed up to   18 1212665295
Last checkpoint at  18 1135877290
0 pending log writes, 0 pending chkp writes
4341 log i/o's done, 1.22 log i/o's/second
----------------------
BUFFER POOL AND MEMORY
----------------------
Total memory allocated 84966343; in additional pool allocated 1402624
Buffer pool size   3200
Free buffers       110
Database pages     3074
Modified db pages  2674
Pending reads 0
Pending writes: LRU 0, flush list 0, single page 0
Pages read 171380, created 51968, written 194688
28.72 reads/s, 20.72 creates/s, 47.55 writes/s
Buffer pool hit rate 999 / 1000
--------------
ROW OPERATIONS
--------------
0 queries inside InnoDB, 0 queries in queue
Main thread process no. 3004, id 7176, state: purging
Number of rows inserted 3738558, updated 127415, deleted 33707, read 755779
1586.13 inserts/s, 50.89 updates/s, 28.44 deletes/s, 107.88 reads/s
----------------------------
END OF INNODB MONITOR OUTPUT
============================

Some notes on the output:

  • If the TRANSACTIONS section reports lock waits, your applications may have lock contention. The output can also help to trace the reasons for transaction deadlocks.

  • The SEMAPHORES section reports threads waiting for a semaphore and statistics on how many times threads have needed a spin or a wait on a mutex or a rw-lock semaphore. A large number of threads waiting for semaphores may be a result of disk I/O, or contention problems inside InnoDB. Contention can be due to heavy parallelism of queries or problems in operating system thread scheduling. Setting innodb_thread_concurrency smaller than the default value can help in such situations.

  • The BUFFER POOL AND MEMORY section gives you statistics on pages read and written. You can calculate from these numbers how many data file I/O operations your queries currently are doing.

  • The ROW OPERATIONS section shows what the main thread is doing.

InnoDB sends diagnostic output to stderr or to files rather than to stdout or fixed-size memory buffers, to avoid potential buffer overflows. As a side effect, the output of SHOW ENGINE INNODB STATUS is written to a status file in the MySQL data directory every fifteen seconds. The name of the file is innodb_status.pid, where pid is the server process ID. InnoDB removes the file for a normal shutdown. If abnormal shutdowns have occurred, instances of these status files may be present and must be removed manually. Before removing them, you might want to examine them to see whether they contain useful information about the cause of abnormal shutdowns. The innodb_status.pid file is created only if the configuration option innodb_status_file=1 is set.

14.5.12. Implementation of Multi-Versioning

Because InnoDB is a multi-versioned storage engine, it must keep information about old versions of rows in the tablespace. This information is stored in a data structure called a rollback segment (after an analogous data structure in Oracle).

Internally, InnoDB adds two fields to each row stored in the database. A 6-byte field indicates the transaction identifier for the last transaction that inserted or updated the row. Also, a deletion is treated internally as an update where a special bit in the row is set to mark it as deleted. Each row also contains a 7-byte field called the roll pointer. The roll pointer points to an undo log record written to the rollback segment. If the row was updated, the undo log record contains the information necessary to rebuild the content of the row before it was updated.

InnoDB uses the information in the rollback segment to perform the undo operations needed in a transaction rollback. It also uses the information to build earlier versions of a row for a consistent read.

Undo logs in the rollback segment are divided into insert and update undo logs. Insert undo logs are needed only in transaction rollback and can be discarded as soon as the transaction commits. Update undo logs are used also in consistent reads, but they can be discarded only after there is no transaction present for which InnoDB has assigned a snapshot that in a consistent read could need the information in the update undo log to build an earlier version of a database row.

You must remember to commit your transactions regularly, including those transactions that issue only consistent reads. Otherwise, InnoDB cannot discard data from the update undo logs, and the rollback segment may grow too big, filling up your tablespace.

The physical size of an undo log record in the rollback segment is typically smaller than the corresponding inserted or updated row. You can use this information to calculate the space need for your rollback segment.

In the InnoDB multi-versioning scheme, a row is not physically removed from the database immediately when you delete it with an SQL statement. Only when InnoDB can discard the update undo log record written for the deletion can it also physically remove the corresponding row and its index records from the database. This removal operation is called a purge, and it is quite fast, usually taking the same order of time as the SQL statement that did the deletion.

In a scenario where the user inserts and deletes rows in smallish batches at about the same rate in the table, it is possible that the purge thread starts to lag behind, and the table grows bigger and bigger, making everything disk-bound and very slow. Even if the table carries just 10MB of useful data, it may grow to occupy 10GB with all the “dead” rows. In such a case, it would be good to throttle new row operations, and allocate more resources to the purge thread. The innodb_max_purge_lag system variable exists for exactly this purpose. See Section 14.5.4, “InnoDB Startup Options and System Variables”, for more information.

14.5.13. InnoDB Table and Index Structures

MySQL stores its data dictionary information for tables in .frm files in database directories. This is true for all MySQL storage engines. But every InnoDB table also has its own entry in the InnoDB internal data dictionary inside the tablespace. When MySQL drops a table or a database, it has to delete both an .frm file or files, and the corresponding entries inside the InnoDB data dictionary. This is the reason why you cannot move InnoDB tables between databases simply by moving the .frm files.

Every InnoDB table has a special index called the clustered index where the data for the rows is stored. If you define a PRIMARY KEY on your table, the index of the primary key is the clustered index.

If you do not define a PRIMARY KEY for your table, MySQL picks the first UNIQUE index that has only NOT NULL columns as the primary key and InnoDB uses it as the clustered index. If there is no such index in the table, InnoDB internally generates a clustered index where the rows are ordered by the row ID that InnoDB assigns to the rows in such a table. The row ID is a 6-byte field that increases monotonically as new rows are inserted. Thus, the rows ordered by the row ID are physically in insertion order.

Accessing a row through the clustered index is fast because the row data is on the same page where the index search leads. If a table is large, the clustered index architecture often saves a disk I/O when compared to the traditional solution. (In many database systems, data storage uses a different page from the index record.)

In InnoDB, the records in non-clustered indexes (also called secondary indexes) contain the primary key value for the row. InnoDB uses this primary key value to search for the row from the clustered index. Note that if the primary key is long, the secondary indexes use more space.

InnoDB compares CHAR and VARCHAR strings of different lengths such that the remaining length in the shorter string is treated as if padded with spaces.

14.5.13.1. Physical Structure of an Index

All InnoDB indexes are B-trees where the index records are stored in the leaf pages of the tree. The default size of an index page is 16KB. When new records are inserted, InnoDB tries to leave 1/16 of the page free for future insertions and updates of the index records.

If index records are inserted in a sequential order (ascending or descending), the resulting index pages are about 15/16 full. If records are inserted in a random order, the pages are from 1/2 to 15/16 full. If the fill factor of an index page drops below 1/2, InnoDB tries to contract the index tree to free the page.

14.5.13.2. Insert Buffering

It is a common situation in database applications that the primary key is a unique identifier and new rows are inserted in the ascending order of the primary key. Thus, the insertions to the clustered index do not require random reads from a disk.

On the other hand, secondary indexes are usually non-unique, and insertions into secondary indexes happen in a relatively random order. This would cause a lot of random disk I/O operations without a special mechanism used in InnoDB.

If an index record should be inserted to a non-unique secondary index, InnoDB checks whether the secondary index page is in the buffer pool. If that is the case, InnoDB does the insertion directly to the index page. If the index page is not found in the buffer pool, InnoDB inserts the record to a special insert buffer structure. The insert buffer is kept so small that it fits entirely in the buffer pool, and insertions can be done very fast.

Periodically, the insert buffer is merged into the secondary index trees in the database. Often it is possible to merge several insertions to the same page of the index tree, saving disk I/O operations. It has been measured that the insert buffer can speed up insertions into a table up to 15 times.

The insert buffer merging may continue to happen after the inserting transaction has been committed. In fact, it may continue to happen after a server shutdown and restart (see Section 14.5.8.1, “Forcing InnoDB Recovery”).

The insert buffer merging may take many hours, when many secondary indexes must be updated, and many rows have been inserted. During this time, disk I/O will be increased, which can cause significant slowdown on disk-bound queries. Another significant background I/O operation is the purge thread (see Section 14.5.12, “Implementation of Multi-Versioning”).

14.5.13.3. Adaptive Hash Indexes

If a table fits almost entirely in main memory, the fastest way to perform queries on it is to use hash indexes. InnoDB has a mechanism that monitors index searches made to the indexes defined for a table. If InnoDB notices that queries could benefit from building a hash index, it does so automatically.

Note that the hash index is always built based on an existing B-tree index on the table. InnoDB can build a hash index on a prefix of any length of the key defined for the B-tree, depending on the pattern of searches that InnoDB observes for the B-tree index. A hash index can be partial: It is not required that the whole B-tree index is cached in the buffer pool. InnoDB builds hash indexes on demand for those pages of the index that are often accessed.

In a sense, InnoDB tailors itself through the adaptive hash index mechanism to ample main memory, coming closer to the architecture of main-memory databases.

14.5.13.4. Physical Row Structure

The physical record structure for InnoDB tables is dependent on the row format specified when the table was created. For MySQL 5.1, by default InnoDB uses the COMPACT format, but the REDUNDANT format is available to retain compatibility with older versions of MySQL.

Records in InnoDB ROW_FORMAT=REDUNDANT tables have the following characteristics:

  • Each index record contains a six-byte header. The header is used to link together consecutive records, and also in row-level locking.

  • Records in the clustered index contain fields for all user-defined columns. In addition, there is a six-byte field for the transaction ID and a seven-byte field for the roll pointer.

  • If no primary key was defined for a table, each clustered index record also contains a six-byte row ID field.

  • Each secondary index record contains also all the fields defined for the clustered index key.

  • A record contains also a pointer to each field of the record. If the total length of the fields in a record is less than 128 bytes, the pointer is one byte; otherwise, two bytes. The array of these pointers is called the record directory. The area where these pointers point is called the data part of the record.

  • Internally, InnoDB stores fixed-length character columns such as CHAR(10) in a fixed-length format. InnoDB truncates trailing spaces from VARCHAR columns.

  • An SQL NULL value reserves 1 or 2 bytes in the record directory. Besides that, an SQL NULL value reserves zero bytes in the data part of the record if stored in a variable length column. In a fixed-length column, it reserves the fixed length of the column in the data part of the record. The motivation behind reserving the fixed space for NULL values is that it enables an update of the column from NULL to a non-NULL value to be done in place without causing fragmentation of the index page.

Records in InnoDB ROW_FORMAT=COMPACT tables have the following characteristics:

  • Each index record contains a five-byte header that may be preceded by a variable-length header. The header is used to link together consecutive records, and also in row-level locking.

  • The record header contains a bit vector for indicating NULL columns. The bit vector occupies (n_nullable+7)/8 bytes. Columns that are NULL will not occupy other space than the bit in this vector.

  • For each non-NULL variable-length field, the record header contains the length of the column in one or two bytes. Two bytes will only be needed if part of the column is stored externally or the maximum length exceeds 255 bytes and the actual length exceeds 127 bytes.

  • The record header is followed by the data contents of the columns. Columns that are NULL are omitted.

  • Records in the clustered index contain fields for all user-defined columns. In addition, there is a six-byte field for the transaction ID and a seven-byte field for the roll pointer.

  • If no primary key was defined for a table, each clustered index record also contains a six-byte row ID field.

  • Each secondary index record contains also all the fields defined for the clustered index key.

  • Internally, InnoDB stores fixed-length, fixed-width character columns such as CHAR(10) in a fixed-length format. InnoDB truncates trailing spaces from VARCHAR columns.

  • Internally, InnoDB attempts to store UTF-8 CHAR(n) columns in n bytes by trimming trailing spaces. In ROW_FORMAT=REDUNDANT, such columns occupy 3*n bytes. The motivation behind reserving the minimum space n is that it in many cases enables an update of the column to be done in place without causing fragmentation of the index page.

14.5.14. InnoDB File Space Management and Disk I/O

14.5.14.1. InnoDB Disk I/O

InnoDB uses simulated asynchronous disk I/O: InnoDB creates a number of threads to take care of I/O operations, such as read-ahead.

There are two read-ahead heuristics in InnoDB:

  • In sequential read-ahead, if InnoDB notices that the access pattern to a segment in the tablespace is sequential, it posts in advance a batch of reads of database pages to the I/O system.

  • In random read-ahead, if InnoDB notices that some area in a tablespace seems to be in the process of being fully read into the buffer pool, it posts the remaining reads to the I/O system.

InnoDB uses a novel file flush technique called doublewrite. It adds safety to recovery following an operating system crash or a power outage, and improves performance on most varieties of Unix by reducing the need for fsync() operations.

Doublewrite means that before writing pages to a data file, InnoDB first writes them to a contiguous tablespace area called the doublewrite buffer. Only after the write and the flush to the doublewrite buffer has completed does InnoDB write the pages to their proper positions in the data file. If the operating system crashes in the middle of a page write, InnoDB can later find a good copy of the page from the doublewrite buffer during recovery.

14.5.14.2. File Space Management

The data files that you define in the configuration file form the tablespace of InnoDB. The files are simply concatenated to form the tablespace. There is no striping in use. Currently, you cannot define where within the tablespace your tables are allocated. However, in a newly created tablespace, InnoDB allocates space starting from the first data file.

The tablespace consists of database pages with a default size of 16KB. The pages are grouped into extents of 64 consecutive pages. The “files” inside a tablespace are called segments in InnoDB. The term “rollback segment” is somewhat confusing because it actually contains many tablespace segments.

Two segments are allocated for each index in InnoDB. One is for non-leaf nodes of the B-tree, the other is for the leaf nodes. The idea here is to achieve better sequentiality for the leaf nodes, which contain the data.

When a segment grows inside the tablespace, InnoDB allocates the first 32 pages to it individually. After that InnoDB starts to allocate whole extents to the segment. InnoDB can add to a large segment up to 4 extents at a time to ensure good sequentiality of data.

Some pages in the tablespace contain bitmaps of other pages, and therefore a few extents in an InnoDB tablespace cannot be allocated to segments as a whole, but only as individual pages.

When you ask for available free space in the tablespace by issuing a SHOW TABLE STATUS statement, InnoDB reports the extents that are definitely free in the tablespace. InnoDB always reserves some extents for cleanup and other internal purposes; these reserved extents are not included in the free space.

When you delete data from a table, InnoDB contracts the corresponding B-tree indexes. Whether the freed space becomes available for other users depends on whether the pattern of deletes frees individual pages or extents to the tablespace. Dropping a table or deleting all rows from it is guaranteed to release the space to other users, but remember that deleted rows are physically removed only in an (automatic) purge operation after they are no longer needed for transaction rollbacks or consistent reads. (See Section 14.5.12, “Implementation of Multi-Versioning”.)

14.5.14.3. Defragmenting a Table

If there are random insertions into or deletions from the indexes of a table, the indexes may become fragmented. Fragmentation means that the physical ordering of the index pages on the disk is not close to the index ordering of the records on the pages, or that there are many unused pages in the 64-page blocks that were allocated to the index.

A symptom of fragmentation is that a table takes more space than it “should” take. How much that is exactly, is difficult to determine. All InnoDB data and indexes are stored in B-trees, and their fill factor may vary from 50% to 100%. Another symptom of fragmentation is that a table scan such as this takes more time than it “should” take:

SELECT COUNT(*) FROM t WHERE a_non_indexed_column <> 12345;

(In the preceding query, we are “fooling” the SQL optimizer into scanning the clustered index, rather than a secondary index.) Most disks can read 10 to 50MB/s, which can be used to estimate how fast a table scan should run.

It can speed up index scans if you periodically perform a “nullALTER TABLE operation:

ALTER TABLE tbl_name ENGINE=INNODB

That causes MySQL to rebuild the table. Another way to perform a defragmentation operation is to use mysqldump to dump the table to a text file, drop the table, and reload it from the dump file.

If the insertions to an index are always ascending and records are deleted only from the end, the InnoDB filespace management algorithm guarantees that fragmentation in the index does not occur.

14.5.15. InnoDB Error Handling

Error handling in InnoDB is not always the same as specified in the SQL standard. According to the standard, any error during an SQL statement should cause the rollback of that statement. InnoDB sometimes rolls back only part of the statement, or the whole transaction. The following items describe how InnoDB performs error handling:

  • If you run out of file space in the tablespace, a MySQL Table is full error occurs and InnoDB rolls back the SQL statement.

  • A transaction deadlock causes InnoDB to roll back the entire transaction. In the case of a lock wait timeout, InnoDB rolls back only the most recent SQL statement.

    When a transaction rollback occurs due to a deadlock or lock wait timeout, it cancels the effect of the statements within the transaction. But if the start-transaction statement was START TRANSACTION or BEGIN statement, rollback does not cancel that statement. Further SQL statements become part of the transaction until the occurrence of COMMIT, ROLLBACK, or some SQL statement that causes an implicit commit.

  • A duplicate-key error rolls back the SQL statement, if you have not specified the IGNORE option in your statement.

  • A row too long error rolls back the SQL statement.

  • Other errors are mostly detected by the MySQL layer of code (above the InnoDB storage engine level), and they roll back the corresponding SQL statement. Locks are not released in a rollback of a single SQL statement.

During implicit rollbacks, as well as during the execution of an explicit ROLLBACK SQL command, SHOW PROCESSLIST displays Rolling back in the State column for the relevant connection.

14.5.15.1. InnoDB Error Codes

The following is a non-exhaustive list of common InnoDB-specific errors that you may encounter, with information about why each occurs and how to resolve the problem.

  • 1005 (ER_CANT_CREATE_TABLE)

    Cannot create table. If the error message refers to errno 150, table creation failed because a foreign key constraint was not correctly formed. If the error message refers to errno -1, table creation probably failed because the table includes a column name that matched the name of an internal InnoDB table.

  • 1016 (ER_CANT_OPEN_FILE)

    Cannot find the InnoDB table from the InnoDB data files, although the .frm file for the table exists. See Section 14.5.17.1, “Troubleshooting InnoDB Data Dictionary Operations”.

  • 1114 (ER_RECORD_FILE_FULL)

    InnoDB has run out of free space in the tablespace. You should reconfigure the tablespace to add a new data file.

  • 1205 (ER_LOCK_WAIT_TIMEOUT)

    Lock wait timeout expired. Transaction was rolled back.

  • 1213 (ER_LOCK_DEADLOCK)

    Transaction deadlock. You should rerun the transaction.

  • 1216 (ER_NO_REFERENCED_ROW)

    You are trying to add a row but there is no parent row, and a foreign key constraint fails. You should add the parent row first.

  • 1217 (ER_ROW_IS_REFERENCED)

    You are trying to delete a parent row that has children, and a foreign key constraint fails. You should delete the children first.

14.5.15.2. Operating System Error Codes

To print the meaning of an operating system error number, use the perror program that comes with the MySQL distribution.

The following table provides a list of some common Linux system error codes. For a more complete list, see Linux source code.

  • 1 (EPERM)

    Operation not permitted

  • 2 (ENOENT)

    No such file or directory

  • 3 (ESRCH)

    No such process

  • 4 (EINTR)

    Interrupted system call

  • 5 (EIO)

    I/O error

  • 6 (ENXIO)

    No such device or address

  • 7 (E2BIG)

    Arg list too long

  • 8 (ENOEXEC)

    Exec format error

  • 9 (EBADF)

    Bad file number

  • 10 (ECHILD)

    No child processes

  • 11 (EAGAIN)

    Try again

  • 12 (ENOMEM)

    Out of memory

  • 13 (EACCES)

    Permission denied

  • 14 (EFAULT)

    Bad address

  • 15 (ENOTBLK)

    Block device required

  • 16 (EBUSY)

    Device or resource busy

  • 17 (EEXIST)

    File exists

  • 18 (EXDEV)

    Cross-device link

  • 19 (ENODEV)

    No such device

  • 20 (ENOTDIR)

    Not a directory

  • 21 (EISDIR)

    Is a directory

  • 22 (EINVAL)

    Invalid argument

  • 23 (ENFILE)

    File table overflow

  • 24 (EMFILE)

    Too many open files

  • 25 (ENOTTY)

    Inappropriate ioctl for device

  • 26 (ETXTBSY)

    Text file busy

  • 27 (EFBIG)

    File too large

  • 28 (ENOSPC)

    No space left on device

  • 29 (ESPIPE)

    Illegal seek

  • 30 (EROFS)

    Read-only file system

  • 31 (EMLINK)

    Too many links

The following table provides a list of some common Windows system error codes. For a complete list see the Microsoft Web site.

  • 1 (ERROR_INVALID_FUNCTION)

    Incorrect function.

  • 2 (ERROR_FILE_NOT_FOUND)

    The system cannot find the file specified.

  • 3 (ERROR_PATH_NOT_FOUND)

    The system cannot find the path specified.

  • 4 (ERROR_TOO_MANY_OPEN_FILES)

    The system cannot open the file.

  • 5 (ERROR_ACCESS_DENIED)

    Access is denied.

  • 6 (ERROR_INVALID_HANDLE)

    The handle is invalid.

  • 7 (ERROR_ARENA_TRASHED)

    The storage control blocks were destroyed.

  • 8 (ERROR_NOT_ENOUGH_MEMORY)

    Not enough storage is available to process this command.

  • 9 (ERROR_INVALID_BLOCK)

    The storage control block address is invalid.

  • 10 (ERROR_BAD_ENVIRONMENT)

    The environment is incorrect.

  • 11 (ERROR_BAD_FORMAT)

    An attempt was made to load a program with an incorrect format.

  • 12 (ERROR_INVALID_ACCESS)

    The access code is invalid.

  • 13 (ERROR_INVALID_DATA)

    The data is invalid.

  • 14 (ERROR_OUTOFMEMORY)

    Not enough storage is available to complete this operation.

  • 15 (ERROR_INVALID_DRIVE)

    The system cannot find the drive specified.

  • 16 (ERROR_CURRENT_DIRECTORY)

    The directory cannot be removed.

  • 17 (ERROR_NOT_SAME_DEVICE)

    The system cannot move the file to a different disk drive.

  • 18 (ERROR_NO_MORE_FILES)

    There are no more files.

  • 19 (ERROR_WRITE_PROTECT)

    The media is write protected.

  • 20 (ERROR_BAD_UNIT)

    The system cannot find the device specified.

  • 21 (ERROR_NOT_READY)

    The device is not ready.

  • 22 (ERROR_BAD_COMMAND)

    The device does not recognize the command.

  • 23 (ERROR_CRC)

    Data error (cyclic redundancy check).

  • 24 (ERROR_BAD_LENGTH)

    The program issued a command but the command length is incorrect.

  • 25 (ERROR_SEEK)

    The drive cannot locate a specific area or track on the disk.

  • 26 (ERROR_NOT_DOS_DISK)

    The specified disk or diskette cannot be accessed.

  • 27 (ERROR_SECTOR_NOT_FOUND)

    The drive cannot find the sector requested.

  • 28 (ERROR_OUT_OF_PAPER)

    The printer is out of paper.

  • 29 (ERROR_WRITE_FAULT)

    The system cannot write to the specified device.

  • 30 (ERROR_READ_FAULT)

    The system cannot read from the specified device.

  • 31 (ERROR_GEN_FAILURE)

    A device attached to the system is not functioning.

  • 32 (ERROR_SHARING_VIOLATION)

    The process cannot access the file because it is being used by another process.

  • 33 (ERROR_LOCK_VIOLATION)

    The process cannot access the file because another process has locked a portion of the file.

  • 34 (ERROR_WRONG_DISK)

    The wrong diskette is in the drive. Insert %2 (Volume Serial Number: %3) into drive %1.

  • 36 (ERROR_SHARING_BUFFER_EXCEEDED)

    Too many files opened for sharing.

  • 38 (ERROR_HANDLE_EOF)

    Reached the end of the file.

  • 39 (ERROR_HANDLE_DISK_FULL)

    The disk is full.

  • 87 (ERROR_INVALID_PARAMETER)

    The parameter is incorrect. (If this error occurs on Windows and you have enabled innodb_file_per_table in a server option file, add the line innodb_flush_method=unbuffered to the file as well.)

  • 112 (ERROR_DISK_FULL)

    The disk is full.

  • 123 (ERROR_INVALID_NAME)

    The filename, directory name, or volume label syntax is incorrect.

  • 1450 (ERROR_NO_SYSTEM_RESOURCES)

    Insufficient system resources exist to complete the requested service.

14.5.16. Restrictions on InnoDB Tables

  • Warning: Do not convert MySQL system tables in the mysql database from MyISAM to InnoDB tables! This is an unsupported operation. If you do this, MySQL does not restart until you restore the old system tables from a backup or re-generate them with the mysql_install_db script.

  • A table cannot contain more than 1000 columns.

  • The internal maximum key length is 3500 bytes, but MySQL itself restricts this to 1024 bytes.

  • The maximum row length, except for VARCHAR, BLOB and TEXT columns, is slightly less than half of a database page. That is, the maximum row length is about 8000 bytes. LONGBLOB and LONGTEXT columns must be less than 4GB, and the total row length, including also BLOB and TEXT columns, must be less than 4GB. InnoDB stores the first 768 bytes of a VARCHAR, BLOB, or TEXT column in the row, and the rest into separate pages.

  • Although InnoDB supports row sizes larger than 65535 internally, you cannot define a row containing VARCHAR columns with a combined size larger than 65535:

    mysql> CREATE TABLE t (a VARCHAR(8000), b VARCHAR(10000),
        -> c VARCHAR(10000), d VARCHAR(10000), e VARCHAR(10000),
        -> f VARCHAR(10000), g VARCHAR(10000)) ENGINE=InnoDB;
    ERROR 1118 (42000): Row size too large. The maximum row size for the
    used table type, not counting BLOBs, is 65535. You have to change some
    columns to TEXT or BLOBs
    
  • On some older operating systems, files must be less than 2GB. This is not a limitation of InnoDB itself, but if you require a large tablespace, you will need to configure it using several smaller data files rather than one or a file large data files.

  • The combined size of the InnoDB log files must be less than 4GB.

  • The minimum tablespace size is 10MB. The maximum tablespace size is four billion database pages (64TB). This is also the maximum size for a table.

  • InnoDB tables do not support FULLTEXT indexes.

  • InnoDB tables support spatial types, but not indexes on them.

  • ANALYZE TABLE determines index cardinality (as displayed in the Cardinality column of SHOW INDEX output) by doing ten random dives to each of the index trees and updating index cardinality estimates accordingly. Note that because these are only estimates, repeated runs of ANALYZE TABLE may produce different numbers. This makes ANALYZE TABLE fast on InnoDB tables but not 100% accurate as it doesn't take all rows into account.

    MySQL uses index cardinality estimates only in join optimization. If some join is not optimized in the right way, you can try using ANALYZE TABLE. In the few cases that ANALYZE TABLE doesn't produce values good enough for your particular tables, you can use FORCE INDEX with your queries to force the use of a particular index, or set the max_seeks_for_key system variable to ensure that MySQL prefers index lookups over table scans. See Section 5.2.3, “System Variables”, and Section B.6, “Optimizer-Related Issues”.

  • SHOW TABLE STATUS does not give accurate statistics on InnoDB tables, except for the physical size reserved by the table. The row count is only a rough estimate used in SQL optimization.

  • InnoDB does not keep an internal count of rows in a table. (In practice, this would be somewhat complicated due to multi-versioning.) To process a SELECT COUNT(*) FROM t statement, InnoDB must scan an index of the table, which takes some time if the index is not entirely in the buffer pool. To get a fast count, you have to use a counter table you create yourself and let your application update it according to the inserts and deletes it does. If your table does not change often, using the MySQL query cache is a good solution. SHOW TABLE STATUS also can be used if an approximate row count is sufficient. See Section 14.5.11, “InnoDB Performance Tuning Tips”.

  • On Windows, InnoDB always stores database and table names internally in lowercase. To move databases in binary format from Unix to Windows or from Windows to Unix, you should always use explicitly lowercase names when creating databases and tables.

  • For an AUTO_INCREMENT column, you must always define an index for the table, and that index must contain just the AUTO_INCREMENT column. In MyISAM tables, the AUTO_INCREMENT column may be part of a multi-column index.

  • While initializing a previously specified AUTO_INCREMENT column on a table, InnoDB sets an exclusive lock on the end of the index associated with the AUTO_INCREMENT column. In accessing the auto-increment counter, InnoDB uses a specific table lock mode AUTO-INC where the lock lasts only to the end of the current SQL statement, not to the end of the entire transaction. Note that other clients cannot insert into the table while the AUTO-INC table lock is held; see Section 14.5.10.2, “InnoDB and AUTOCOMMIT.

  • When you restart the MySQL server, InnoDB may reuse an old value that was generated for an AUTO_INCREMENT column but never stored (that is, a value that was generated during an old transaction that was rolled back).

  • When an AUTO_INCREMENT column runs out of values, InnoDB wraps a BIGINT to -9223372036854775808 and BIGINT UNSIGNED to 1. However, BIGINT values have 64 bits, so do note that if you were to insert one million rows per second, it would still take nearly three hundred thousand years before BIGINT reached its upper bound. With all other integer type columns, a duplicate-key error results. This is similar to how MyISAM works, because it is mostly general MySQL behavior and not about any storage engine in particular.

  • DELETE FROM tbl_name does not regenerate the table but instead deletes all rows, one by one.

  • Under some conditions, TRUNCATE tbl_name for an InnoDB table is mapped to DELETE FROM tbl_name and doesn't reset the AUTO_INCREMENT counter. See Section 13.2.9, “TRUNCATE Syntax”.

  • In MySQL 5.1, the MySQL LOCK TABLES operation acquires two locks on each table if innodb_table_locks=1 (the default). In addition to a table lock on the MySQL layer, it also acquires an InnoDB table lock. Older versions of MySQL did not acquire InnoDB table locks; the old behavior can be selected by setting innodb_table_locks=0. If no InnoDB table lock is acquired, LOCK TABLES completes even if some records of the tables are being locked by other transactions.

  • All InnoDB locks held by a transaction are released when the transaction is committed or aborted. Thus, it does not make much sense to invoke LOCK TABLES on InnoDB tables in AUTOCOMMIT=1 mode, because the acquired InnoDB table locks would be released immediately.

  • Sometimes it would be useful to lock further tables in the course of a transaction. Unfortunately, LOCK TABLES in MySQL performs an implicit COMMIT and UNLOCK TABLES. An InnoDB variant of LOCK TABLES has been planned that can be executed in the middle of a transaction.

  • The LOAD TABLE FROM MASTER statement for setting up replication slave servers does not work for InnoDB tables. A workaround is to alter the table to MyISAM on the master, do then the load, and after that alter the master table back to InnoDB. Do not do this if the tables use InnoDB-specific features such as foreign keys.

  • The default database page size in InnoDB is 16KB. By recompiling the code, you can set it to values ranging from 8KB to 64KB. You must update the values of UNIV_PAGE_SIZE and UNIV_PAGE_SIZE_SHIFT in the univ.i source file.

  • Currently, triggers are not activated by cascaded foreign key actions.

14.5.17. InnoDB Troubleshooting

The following general guidelines apply to troubleshooting InnoDB problems:

  • When an operation fails or you suspect a bug, you should look at the MySQL server error log, which is the file in the data directory that has a suffix of .err.

  • When troubleshooting, it is usually best to run the MySQL server from the command prompt, rather than through the mysqld_safe wrapper or as a Windows service. You can then see what mysqld prints to the console, and so have a better grasp of what is going on. On Windows, you must start the server with the --console option to direct the output to the console window.

  • Use the InnoDB Monitors to obtain information about a problem (see Section 14.5.11.1, “SHOW ENGINE INNODB STATUS and the InnoDB Monitors”). If the problem is performance-related, or your server appears to be hung, you should use innodb_monitor to print information about the internal state of InnoDB. If the problem is with locks, use innodb_lock_monitor. If the problem is in creation of tables or other data dictionary operations, use innodb_table_monitor to print the contents of the InnoDB internal data dictionary.

  • If you suspect that a table is corrupt, run CHECK TABLE on that table.

14.5.17.1. Troubleshooting InnoDB Data Dictionary Operations

A specific issue with tables is that the MySQL server keeps data dictionary information in .frm files it stores in the database directories, whereas InnoDB also stores the information into its own data dictionary inside the tablespace files. If you move .frm files around, or if the server crashes in the middle of a data dictionary operation, the locations of the .frm files may end up out of synchrony with the locations recorded in the InnoDB internal data dictionary.

A symptom of an out-of-sync data dictionary is that a CREATE TABLE statement fails. If this occurs, you should look in the server's error log. If the log says that the table already exists inside the InnoDB internal data dictionary, you have an orphaned table inside the InnoDB tablespace files that has no corresponding .frm file. The error message looks like this:

InnoDB: Error: table test/parent already exists in InnoDB internal
InnoDB: data dictionary. Have you deleted the .frm file
InnoDB: and not used DROP TABLE? Have you used DROP DATABASE
InnoDB: for InnoDB tables in MySQL version <= 3.23.43?
InnoDB: See the Restrictions section of the InnoDB manual.
InnoDB: You can drop the orphaned table inside InnoDB by
InnoDB: creating an InnoDB table with the same name in another
InnoDB: database and moving the .frm file to the current database.
InnoDB: Then MySQL thinks the table exists, and DROP TABLE will
InnoDB: succeed.

You can drop the orphaned table by following the instructions given in the error message. If you are still unable to use DROP TABLE successfully, the problem may be due to name completion in the mysql client. To work around this problem, start the mysql client with the --skip-auto-rehash option and try DROP TABLE again. (With name completion on, mysql tries to construct a list of table names, which fails when a problem such as just described exists.)

Another symptom of an out-of-sync data dictionary is that MySQL prints an error that it cannot open a .InnoDB file:

ERROR 1016: Can't open file: 'child2.InnoDB'. (errno: 1)

In the error log you can find a message like this:

InnoDB: Cannot find table test/child2 from the internal data dictionary
InnoDB: of InnoDB though the .frm file for the table exists. Maybe you
InnoDB: have deleted and recreated InnoDB data files but have forgotten
InnoDB: to delete the corresponding .frm files of InnoDB tables?

This means that there is an orphaned .frm file without a corresponding table inside InnoDB. You can drop the orphaned .frm file by deleting it manually.

If MySQL crashes in the middle of an ALTER TABLE operation, you may end up with an orphaned temporary table inside the InnoDB tablespace. Using innodb_table_monitor you can see listed a table whose name is #sql-.... You can perform SQL statements on tables whose name contains the character ‘#’ if you enclose the name within backticks. Thus, you can drop such an orphaned table like any other orphaned table using the method described earlier. Note that to copy or rename a file in the Unix shell, you need to put the file name in double quotes if the file name contains ‘#’.

14.6. The MERGE Storage Engine

The MERGE storage engine, also known as the MRG_MyISAM engine, is a collection of identical MyISAM tables that can be used as one. “Identical” means that all tables have identical column and index information. You cannot merge MyISAM tables in which the columns are listed in a different order, do not have exactly the same columns, or have the indexes in different order. However, any or all of the MyISAM tables can be compressed with myisampack. See Section 8.6, “myisampack — Generate Compressed, Read-Only MyISAM Tables”. Differences in table options such as AVG_ROW_LENGTH, MAX_ROWS, or PACK_KEYS do not matter.

When you create a MERGE table, MySQL creates two files on disk. The files have names that begin with the table name and have an extension to indicate the file type. An .frm file stores the table format, and an .MRG file contains the names of the tables that should be used as one. The tables do not have to be in the same database as the MERGE table itself.

You can use SELECT, DELETE, UPDATE, and INSERT on MERGE tables. You must have SELECT, UPDATE, and DELETE privileges on the MyISAM tables that you map to a MERGE table.

Note: The use of MERGE tables entails the following security issue: If a user has access to MyISAM table t, that user can create a MERGE table m that accesses t. However, if the user's privileges on t are subsequently revoked, the user can continue to access t by doing so through m. If this behavior is undesirable, you can start the server with the new --skip-merge option to disable the MERGE storage engine. This option is available as of MySQL 5.1.12.

If you DROP the MERGE table, you are dropping only the MERGE specification. The underlying tables are not affected.

To create a MERGE table, you must specify a UNION=(list-of-tables) clause that indicates which MyISAM tables you want to use as one. You can optionally specify an INSERT_METHOD option if you want inserts for the MERGE table to take place in the first or last table of the UNION list. Use a value of FIRST or LAST to cause inserts to be made in the first or last table, respectively. If you do not specify an INSERT_METHOD option or if you specify it with a value of NO, attempts to insert rows into the MERGE table result in an error.

The following example shows how to create a MERGE table:

mysql> CREATE TABLE t1 (
    ->    a INT NOT NULL AUTO_INCREMENT PRIMARY KEY,
    ->    message CHAR(20)) ENGINE=MyISAM;
mysql> CREATE TABLE t2 (
    ->    a INT NOT NULL AUTO_INCREMENT PRIMARY KEY,
    ->    message CHAR(20)) ENGINE=MyISAM;
mysql> INSERT INTO t1 (message) VALUES ('Testing'),('table'),('t1');
mysql> INSERT INTO t2 (message) VALUES ('Testing'),('table'),('t2');
mysql> CREATE TABLE total (
    ->    a INT NOT NULL AUTO_INCREMENT,
    ->    message CHAR(20), INDEX(a))
    ->    ENGINE=MERGE UNION=(t1,t2) INSERT_METHOD=LAST;

Note that the a column is indexed as a PRIMARY KEY in the underlying MyISAM tables, but not in the MERGE table. There it is indexed but not as a PRIMARY KEY because a MERGE table cannot enforce uniqueness over the set of underlying tables.

After creating the MERGE table, you can issue queries that operate on the group of tables as a whole:

mysql> SELECT * FROM total;
+---+---------+
| a | message |
+---+---------+
| 1 | Testing |
| 2 | table   |
| 3 | t1      |
| 1 | Testing |
| 2 | table   |
| 3 | t2      |
+---+---------+

To remap a MERGE table to a different collection of MyISAM tables, you can use one of the following methods:

  • DROP the MERGE table and re-create it.

  • Use ALTER TABLE tbl_name UNION=(...) to change the list of underlying tables.

MERGE tables can help you solve the following problems:

  • Easily manage a set of log tables. For example, you can put data from different months into separate tables, compress some of them with myisampack, and then create a MERGE table to use them as one.

  • Obtain more speed. You can split a big read-only table based on some criteria, and then put individual tables on different disks. A MERGE table on this could be much faster than using the big table.

  • Perform more efficient searches. If you know exactly what you are looking for, you can search in just one of the split tables for some queries and use a MERGE table for others. You can even have many different MERGE tables that use overlapping sets of tables.

  • Perform more efficient repairs. It is easier to repair individual tables that are mapped to a MERGE table than to repair a single large table.

  • Instantly map many tables as one. A MERGE table need not maintain an index of its own because it uses the indexes of the individual tables. As a result, MERGE table collections are very fast to create or remap. (Note that you must still specify the index definitions when you create a MERGE table, even though no indexes are created.)

  • If you have a set of tables from which you create a large table on demand, you should instead create a MERGE table on them on demand. This is much faster and saves a lot of disk space.

  • Exceed the file size limit for the operating system. Each MyISAM table is bound by this limit, but a collection of MyISAM tables is not.

  • You can create an alias or synonym for a MyISAM table by defining a MERGE table that maps to that single table. There should be no really notable performance impact from doing this (only a couple of indirect calls and memcpy() calls for each read).

The disadvantages of MERGE tables are:

  • You can use only identical MyISAM tables for a MERGE table.

  • You cannot use a number of MyISAM features in MERGE tables. For example, you cannot create FULLTEXT indexes on MERGE tables. (You can, of course, create FULLTEXT indexes on the underlying MyISAM tables, but you cannot search the MERGE table with a full-text search.)

  • If the MERGE table is non-temporary, all underlying MyISAM tables must be non-temporary, too. If the MERGE table is temporary, the MyISAM tables can be any mix of temporary and non-temporary.

  • MERGE tables use more file descriptors. If 10 clients are using a MERGE table that maps to 10 tables, the server uses (10 × 10) + 10 file descriptors. (10 data file descriptors for each of the 10 clients, and 10 index file descriptors shared among the clients.)

  • Key reads are slower. When you read a key, the MERGE storage engine needs to issue a read on all underlying tables to check which one most closely matches the given key. To read the next key, the MERGE storage engine needs to search the read buffers to find the next key. Only when one key buffer is used up does the storage engine need to read the next key block. This makes MERGE keys much slower on eq_ref searches, but not much slower on ref searches. See Section 7.2.1, “Optimizing Queries with EXPLAIN, for more information about eq_ref and ref.

Additional resources

14.6.1. MERGE Table Problems

The following are known problems with MERGE tables:

  • If you use ALTER TABLE to change a MERGE table to another storage engine, the mapping to the underlying tables is lost. Instead, the rows from the underlying MyISAM tables are copied into the altered table, which then uses the specified storage engine.

  • REPLACE does not work.

  • MERGE tables do not support partitioning. That is, you cannot partition a MERGE table, nor can any of a MERGE table's underlying MyISAM tables be partitioned.

  • You cannot use DROP TABLE, ALTER TABLE, DELETE without a WHERE clause, REPAIR TABLE, TRUNCATE TABLE, OPTIMIZE TABLE, or ANALYZE TABLE on any of the tables that are mapped into an open MERGE table. If you do so, the MERGE table may still refer to the original table, which yields unexpected results. The easiest way to work around this deficiency is to ensure that no MERGE tables remain open by issuing a FLUSH TABLES statement prior to performing any of those operations.

  • DROP TABLE on a table that is in use by a MERGE table does not work on Windows because the MERGE storage engine's table mapping is hidden from the upper layer of MySQL. Windows does not allow open files to be deleted, so you first must flush all MERGE tables (with FLUSH TABLES) or drop the MERGE table before dropping the table.

  • A MERGE table cannot maintain uniqueness constraints over the entire table. When you perform an INSERT, the data goes into the first or last MyISAM table (depending on the value of the INSERT_METHOD option). MySQL ensures that unique key values remain unique within that MyISAM table, but not across all the tables in the collection.

  • When you create or alter MERGE table, there is no check to ensure that the underlying tables are existing MyISAM tables and have identical structures. When the MERGE table is used, MySQL checks that the row length for all mapped tables is equal, but this is not foolproof. If you create a MERGE table from dissimilar MyISAM tables, you are very likely to run into strange problems.

    Similarly, if you create a MERGE table from non-MyISAM tables, or if you drop an underlying table or alter it to be a non-MyISAM table, no error for the MERGE table occurs until later when you attempt to use it.

    Because the underlying MyISAM tables need not exist when the MERGE table is created, you can create the tables in any order, as long as you do not use the MERGE table until all of its underlying tables are in place. Also, if you can ensure that a MERGE table will not be used during a given period, you can perform maintenance operations on the underlying tables, such as backing up or restoring them, altering them, or dropping and recreating them. It is not necessary to redefine the MERGE table temporarily to exclude the underlying tables while you are operating on them.

  • The order of indexes in the MERGE table and its underlying tables should be the same. If you use ALTER TABLE to add a UNIQUE index to a table used in a MERGE table, and then use ALTER TABLE to add a non-unique index on the MERGE table, the index ordering is different for the tables if there was already a non-unique index in the underlying table. (This happens because ALTER TABLE puts UNIQUE indexes before non-unique indexes to facilitate rapid detection of duplicate keys.) Consequently, queries on tables with such indexes may return unexpected results.

  • If you encounter an error message similar to ERROR 1017 (HY000): Can't find file: 'mm.MRG' (errno: 2) it generally indicates that some of the base tables are not using the MyISAM storage engine. Confirm that all tables are MyISAM.

  • There is a limit of 232 (~4.295E+09) rows to a MERGE table, just as there is with a MyISAM, it is therefore not possible to merge multiple MyISAM tables that exceed this limitation. However, you build MySQL with the --with-big-tables option then the row limitation is increased to (232)2 (1.844E+19) rows. See Section 2.9.2, “Typical configure Options”. Beginning with MySQL 5.0.4 all standard binaries are built with this option.

14.7. The MEMORY (HEAP) Storage Engine

The MEMORY storage engine creates tables with contents that are stored in memory. Formerly, these were known as HEAP tables. MEMORY is the preferred term, although HEAP remains supported for backward compatibility.

Each MEMORY table is associated with one disk file. The filename begins with the table name and has an extension of .frm to indicate that it stores the table definition.

To specify explicitly that you want to create a MEMORY table, indicate that with an ENGINE table option:

CREATE TABLE t (i INT) ENGINE = MEMORY;

As indicated by the name, MEMORY tables are stored in memory. They use hash indexes by default, which makes them very fast, and very useful for creating temporary tables. However, when the server shuts down, all rows stored in MEMORY tables are lost. The tables themselves continue to exist because their definitions are stored in .frm files on disk, but they are empty when the server restarts.

This example shows how you might create, use, and remove a MEMORY table:

mysql> CREATE TABLE test ENGINE=MEMORY
    ->     SELECT ip,SUM(downloads) AS down
    ->     FROM log_table GROUP BY ip;
mysql> SELECT COUNT(ip),AVG(down) FROM test;
mysql> DROP TABLE test;

MEMORY tables have the following characteristics:

  • Space for MEMORY tables is allocated in small blocks. Tables use 100% dynamic hashing for inserts. No overflow area or extra key space is needed. No extra space is needed for free lists. Deleted rows are put in a linked list and are reused when you insert new data into the table. MEMORY tables also have none of the problems commonly associated with deletes plus inserts in hashed tables.

  • MEMORY tables can have up to 32 indexes per table, 16 columns per index and a maximum key length of 500 bytes.

  • The MEMORY storage engine implements both HASH and BTREE indexes. You can specify one or the other for a given index by adding a USING clause as shown here:

    CREATE TABLE lookup
        (id INT, INDEX USING HASH (id))
        ENGINE = MEMORY;
    CREATE TABLE lookup
        (id INT, INDEX USING BTREE (id))
        ENGINE = MEMORY;
    

    General characteristics of B-tree and hash indexes are described in Section 7.4.5, “How MySQL Uses Indexes”.

  • You can have non-unique keys in a MEMORY table. (This is an uncommon feature for implementations of hash indexes.)

  • If you have a hash index on a MEMORY table that has a high degree of key duplication (many index entries containing the same value), updates to the table that affect key values and all deletes are significantly slower. The degree of this slowdown is proportional to the degree of duplication (or, inversely proportional to the index cardinality). You can use a BTREE index to avoid this problem.

  • Columns that are indexed can contain NULL values.

  • MEMORY tables use a fixed-length row storage format.

  • MEMORY tables cannot contain BLOB or TEXT columns.

  • MEMORY includes support for AUTO_INCREMENT columns.

  • You can use INSERT DELAYED with MEMORY tables. See Section 13.2.4.2, “INSERT DELAYED Syntax”.

  • MEMORY tables are shared among all clients (just like any other non-TEMPORARY table).

  • MEMORY table contents are stored in memory, which is a property that MEMORY tables share with internal tables that the server creates on the fly while processing queries. However, the two types of tables differ in that MEMORY tables are not subject to storage conversion, whereas internal tables are:

    • If an internal table becomes too large, the server automatically converts it to an on-disk table. The size limit is determined by the value of the tmp_table_size system variable.

    • MEMORY tables are never converted to disk tables. To ensure that you don't accidentally do anything foolish, you can set the max_heap_table_size system variable to impose a maximum size on MEMORY tables. For individual tables, you can also specify a MAX_ROWS table option in the CREATE TABLE statement.

  • The server needs sufficient memory to maintain all MEMORY tables that are in use at the same time.

  • To free memory used by a MEMORY table when you no longer require its contents, you should execute DELETE or TRUNCATE TABLE, or remove the table altogether using DROP TABLE.

  • If you want to populate a MEMORY table when the MySQL server starts, you can use the --init-file option. For example, you can put statements such as INSERT INTO ... SELECT or LOAD DATA INFILE into this file to load the table from a persistent data source. See Section 5.2.2, “Command Options”, and Section 13.2.5, “LOAD DATA INFILE Syntax”.

  • If you are using replication, the master server's MEMORY tables become empty when it is shut down and restarted. However, a slave is not aware that these tables have become empty, so it returns out-of-date content if you select data from them. When a MEMORY table is used on the master for the first time since the master was started, a DELETE statement is written to the master's binary log automatically, thus synchronizing the slave to the master again. Note that even with this strategy, the slave still has outdated data in the table during the interval between the master's restart and its first use of the table. However, if you use the --init-file option to populate the MEMORY table on the master at startup, it ensures that this time interval is zero.

  • The memory needed for one row in a MEMORY table is calculated using the following expression:

    SUM_OVER_ALL_BTREE_KEYS(max_length_of_key + sizeof(char*) × 4)
    + SUM_OVER_ALL_HASH_KEYS(sizeof(char*) × 2)
    + ALIGN(length_of_row+1, sizeof(char*))
    

    ALIGN() represents a round-up factor to cause the row length to be an exact multiple of the char pointer size. sizeof(char*) is 4 on 32-bit machines and 8 on 64-bit machines.

Additional resources

14.8. The EXAMPLE Storage Engine

The EXAMPLE storage engine is a stub engine that does nothing. Its purpose is to serve as an example in the MySQL source code that illustrates how to begin writing new storage engines. As such, it is primarily of interest to developers.

The EXAMPLE storage engine is included in MySQL-Max binary distributions. To enable this storage engine if you build MySQL from source, invoke configure with the --with-example-storage-engine option.

To examine the source for the EXAMPLE engine, look in the storage/example directory of a MySQL source distribution.

When you create an EXAMPLE table, the server creates a table format file in the database directory. The file begins with the table name and has an .frm extension. No other files are created. No data can be stored into the table. Retrievals return an empty result.

mysql> CREATE TABLE test (i INT) ENGINE = EXAMPLE;
Query OK, 0 rows affected (0.78 sec)

mysql> INSERT INTO test VALUES(1),(2),(3);
ERROR 1031 (HY000): Table storage engine for 'test' doesn't »
                    have this option

mysql> SELECT * FROM test;
Empty set (0.31 sec)

The EXAMPLE storage engine does not support indexing.

14.9. The FEDERATED Storage Engine

The FEDERATED storage engine accesses data in tables of remote databases rather than in local tables.

The FEDERATED storage engine is included in MySQL-Max binary distributions. To enable this storage engine if you build MySQL from source, invoke configure with the --with-federated-storage-engine option.

To examine the source for the FEDERATED engine, look in the sql directory of a MySQL source distribution.

Additional resources

14.9.1. Description of the FEDERATED Storage Engine

When you create a FEDERATED table, the server creates a table format file in the database directory. The file begins with the table name and has an .frm extension. No other files are created, because the actual data is in a remote table. This differs from the way that storage engines for local tables work.

For local database tables, data files are local. For example, if you create a MyISAM table named users, the MyISAM handler creates a data file named users.MYD. A handler for local tables reads, inserts, deletes, and updates data in local data files, and rows are stored in a format particular to the handler. To read rows, the handler must parse data into columns. To write rows, column values must be converted to the row format used by the handler and written to the local data file.

With the MySQL FEDERATED storage engine, there are no local data files for a table (for example, there is no .MYD file). Instead, a remote database stores the data that normally would be in the table. The local server connects to a remote server, and uses the MySQL client API to read, delete, update, and insert data in the remote table. Data retrieval is initiated via a SELECT * FROM tbl_name SQL statement. To read the result, rows are fetched one at a time by using the mysql_fetch_row() C API function, and then converting the columns in the SELECT result set to the format that the FEDERATED handler expects.

The flow of information is as follows:

  1. SQL calls issued locally

  2. MySQL handler API (data in handler format)

  3. MySQL client API (data converted to SQL calls)

  4. Remote database -> MySQL client API

  5. Convert result sets (if any) to handler format

  6. Handler API -> Result rows or rows-affected count to local

14.9.2. How to use FEDERATED Tables

The procedure for using FEDERATED tables is very simple. Normally, you have two servers running, either both on the same host or on different hosts. (It is possible for a FEDERATED table to use another table that is managed by the same server, although there is little point in doing so.)

First, you must have a table on the remote server that you want to access by using a FEDERATED table. Suppose that the remote table is in the federated database and is defined like this:

CREATE TABLE test_table (
    id     INT(20) NOT NULL AUTO_INCREMENT,
    name   VARCHAR(32) NOT NULL DEFAULT '',
    other  INT(20) NOT NULL DEFAULT '0',
    PRIMARY KEY  (id),
    INDEX name (name),
    INDEX other_key (other)
)
ENGINE=MyISAM
DEFAULT CHARSET=latin1;

The example uses a MyISAM table, but the table could use any storage engine.

Next, create a FEDERATED table on the local server for accessing the remote table:

CREATE TABLE federated_table (
    id     INT(20) NOT NULL AUTO_INCREMENT,
    name   VARCHAR(32) NOT NULL DEFAULT '',
    other  INT(20) NOT NULL DEFAULT '0',
    PRIMARY KEY  (id),
    INDEX name (name),
    INDEX other_key (other)
)
ENGINE=FEDERATED
DEFAULT CHARSET=latin1
CONNECTION='mysql://root@remote_host:9306/federated/test_table';

(Note: CONNECTION replaces the COMMENT used in some previous versions of MySQL.)

The structure of this table must be exactly the same as that of the remote table, except that the ENGINE table option should be FEDERATED and the CONNECTION table option is a connection string that indicates to the FEDERATED engine how to connect to the remote server.

The FEDERATED engine creates only the test_table.frm file in the federated database.

The remote host information indicates the remote server to which your local server connects, and the database and table information indicates which remote table to use as the data source. In this example, the remote server is indicated to be running as remote_host on port 9306, so there must be a MySQL server running on the remote host and listening to port 9306.

The general form of the connection string in the CONNECTION option is as follows:

scheme://user_name[:password]@host_name[:port_num]/db_name/tbl_name

Only mysql is supported as the scheme value at this point; the password and port number are optional.

Here are some example connection strings:

CONNECTION='mysql://username:password@hostname:port/database/tablename'
CONNECTION='mysql://username@hostname/database/tablename'
CONNECTION='mysql://username:password@hostname/database/tablename'

The use of CONNECTION for specifying the connection string is non-optimal and is likely to change in future. Keep this in mind for applications that use FEDERATED tables. Such applications are likely to need modification if the format for specifying connection information changes.

Because any password given in the connection string is stored as plain text, it can be seen by any user who can use SHOW CREATE TABLE or SHOW TABLE STATUS for the FEDERATED table, or query the TABLES table in the INFORMATION_SCHEMA database.

14.9.3. Limitations of the FEDERATED Storage Engine

The following items indicate features that the FEDERATED storage engine does and does not support:

  • In the first version, the remote server must be a MySQL server. Support by FEDERATED for other database engines may be added in the future.

  • The remote table that a FEDERATED table points to must exist before you try to access the table through the FEDERATED table.

  • It is possible for one FEDERATED table to point to another, but you must be careful not to create a loop.

  • Performance on a FEDERATED table when performing bulk inserts (for example, on a INSERT INTO ... SELECT ... statement) is slower than with other table types because each selected row is treated as an individual INSERT statement on the federated table.

  • Transactions are supported, but distributed transactions (XA) are not currently supported.

  • There is no way for the FEDERATED engine to know if the remote table has changed. The reason for this is that this table must work like a data file that would never be written to by anything other than the database. The integrity of the data in the local table could be breached if there was any change to the remote database.

  • The FEDERATED storage engine supports SELECT, INSERT, UPDATE, DELETE, TRUNCATE, and indexes. It does not support ALTER TABLE, or any Data Definition Language statements other than DROP TABLE. The current implementation does not use prepared statements.

  • The INSERT_ID and TIMESTAMP options are not propagated to the data provider.

  • Any DROP TABLE statement issued against a FEDERATED table will only drop the local table, not the remote table.

  • The implementation uses SELECT, INSERT, UPDATE, and DELETE, but not HANDLER.

  • FEDERATED tables do not work with the query cache.

Some of these limitations may be lifted in future versions of the FEDERATED handler.

14.10. The ARCHIVE Storage Engine

The ARCHIVE storage engine is used for storing large amounts of data without indexes in a very small footprint.

The ARCHIVE storage engine is included in MySQL binary distributions. To enable this storage engine if you build MySQL from source, invoke configure with the --with-archive-storage-engine option.

To examine the source for the ARCHIVE engine, look in the storage/archive directory of a MySQL source distribution.

You can check whether the ARCHIVE storage engine is available with this statement:

mysql> SHOW VARIABLES LIKE 'have_archive';

When you create an ARCHIVE table, the server creates a table format file in the database directory. The file begins with the table name and has an .frm extension. The storage engine creates other files, all having names beginning with the table name. The data and metadata files have extensions of .ARZ and .ARM, respectively. An .ARN file may appear during optimization operations.

The ARCHIVE engine supports INSERT and SELECT, but not DELETE, REPLACE, or UPDATE. It does support ORDER BY operations, BLOB columns, and basically all but spatial data types (see Section 17.4.1, “MySQL Spatial Data Types”). The ARCHIVE engine uses row-level locking.

As of MySQL 5.1.6, the ARCHIVE engine supports the AUTO_INCREMENT column attribute. The AUTO_INCREMENT columns can have either a unique or non-unique index. Attempting to create an index on any other column results in an error. The ARCHIVE engine also supports the AUTO_INCREMENT table option in CREATE TABLE and ALTER TABLE statements to specify the initial sequence value for a new table or reset the sequence value for an existing table, respectively.

As of MySQL 5.1.6, the ARCHIVE engine ignores BLOB columns if they are not requested and scans past them while reading. Formerly, the following two statements had the same cost, but as of 5.1.6, the second is much more efficient than the first:

SELECT a, b, blob_col FROM archive_table;
SELECT a, b FROM archive_table;

Storage: Rows are compressed as they are inserted. The ARCHIVE engine uses zlib lossless data compression (see http://www.zlib.net/). You can use OPTIMIZE TABLE to analyze the table and pack it into a smaller format (for a reason to use OPTIMIZE TABLE, see later in this section). The engine also supports CHECK TABLE. There are several types of insertions that are used:

  • An INSERT statement just pushes rows into a compression buffer, and that buffer flushes as necessary. The insertion into the buffer is protected by a lock. A SELECT forces a flush to occur, unless the only insertions that have come in were INSERT DELAYED (those flush as necessary). See Section 13.2.4.2, “INSERT DELAYED Syntax”.

  • A bulk insert is visible only after it completes, unless other inserts occur at the same time, in which case it can be seen partially. A SELECT never causes a flush of a bulk insert unless a normal insert occurs while it is loading.

Retrieval: On retrieval, rows are uncompressed on demand; there is no row cache. A SELECT operation performs a complete table scan: When a SELECT occurs, it finds out how many rows are currently available and reads that number of rows. SELECT is performed as a consistent read. Note that lots of SELECT statements during insertion can deteriorate the compression, unless only bulk or delayed inserts are used. To achieve better compression, you can use OPTIMIZE TABLE or REPAIR TABLE. The number of rows in ARCHIVE tables reported by SHOW TABLE STATUS is always accurate. See Section 13.5.2.5, “OPTIMIZE TABLE Syntax”, Section 13.5.2.6, “REPAIR TABLE Syntax”, and Section 13.5.4.27, “SHOW TABLE STATUS Syntax”.

Additional resources

14.11. The CSV Storage Engine

The CSV storage engine stores data in text files using comma-separated values format.

To enable this storage engine, use the --with-csv-storage-engine option to configure when you build MySQL.

The CSV storage engine is included in MySQL-Max binary distributions. To enable this storage engine if you build MySQL from source, invoke configure with the --with-csv-storage-engine option.

To examine the source for the CSV engine, look in the storage/csv directory of a MySQL source distribution.

When you create a CSV table, the server creates a table format file in the database directory. The file begins with the table name and has an .frm extension. The storage engine also creates a data file. Its name begins with the table name and has a .CSV extension. The data file is a plain text file. When you store data into the table, the storage engine saves it into the data file in comma-separated values format.

mysql> CREATE TABLE test(i INT, c CHAR(10)) ENGINE = CSV;
Query OK, 0 rows affected (0.12 sec)

mysql> INSERT INTO test VALUES(1,'record one'),(2,'record two');
Query OK, 2 rows affected (0.00 sec)
Records: 2  Duplicates: 0  Warnings: 0

mysql> SELECT * FROM test;
+------+------------+
| i    | c          |
+------+------------+
|    1 | record one |
|    2 | record two |
+------+------------+
2 rows in set (0.00 sec)

Starting with MySQL 5.1.9, creating a CSV table also creates a corresponding Meta-file that stores the state of the table and the number of rows that exist in the table. The name of this file is the same as the name of the table with the extension CSM.

If you examine the test.CSV file in the database directory created by executing the preceding statements, its contents should look like this:

"1","record one"
"2","record two"

This format can be read, and even written, by spreadsheet applications such as Microsoft Excel or StarOffice Calc.

14.11.1. Repairing and Checking CSV Tables

Functionality introduced in version 5.1.9

The CSV storage engines supports the CHECK and REPAIR commands to verify and if possible repair a damaged CSV table.

When running the CHECK command, the CSV file will be checked for validity by looking for the correct field separators, escaped fields (matching quotes and/or missing quotes), the correct number of fields compared to the table definition and the existence of a corresponding CSV metafile. The first invalid row discovered will report an error. Checking a valid table produces output like that shown below:

mysql> check table csvtest;
+--------------+-------+----------+----------+
| Table        | Op    | Msg_type | Msg_text |
+--------------+-------+----------+----------+
| test.csvtest | check | status   | OK       | 
+--------------+-------+----------+----------+
1 row in set (0.00 sec)

A check on a corrupted table returns a fault:

mysql> check table csvtest;
+--------------+-------+----------+----------+
| Table        | Op    | Msg_type | Msg_text |
+--------------+-------+----------+----------+
| test.csvtest | check | error    | Corrupt  | 
+--------------+-------+----------+----------+
1 row in set (0.01 sec)

If the check fails, the table is marked as crashed (corrupt). Once a table has been marked as corrupt, it is automatically repaired when you next run CHECK or execute a SELECT statement. The corresponding corrupt status and new status will be displayed when running CHECK:

mysql> check table csvtest;
+--------------+-------+----------+----------------------------+
| Table        | Op    | Msg_type | Msg_text                   |
+--------------+-------+----------+----------------------------+
| test.csvtest | check | warning  | Table is marked as crashed | 
| test.csvtest | check | status   | OK                         | 
+--------------+-------+----------+----------------------------+
2 rows in set (0.08 sec)

To repair a table you can use REPAIR, this copies as many valid rows from the existing CSV data as possible, and then replaces the existing CSV file with the recovered rows. Any rows beyond the corrupted data are lost.

mysql> repair table csvtest;
+--------------+--------+----------+----------+
| Table        | Op     | Msg_type | Msg_text |
+--------------+--------+----------+----------+
| test.csvtest | repair | status   | OK       | 
+--------------+--------+----------+----------+
1 row in set (0.02 sec)

Warning

Note that during repair, only the rows from the CSV file up to the first damaged row are copied to the new table. All other rows, even valid rows, up to the first damaged row are removed.

14.11.2. CSV Limitations

Important: The CSV storage engine does not support indexing.

Partitioning is not supported for tables using the CSV storage engine. Beginning with MySQL 5.1.12, it is no longer possible to create partitioned CSV tables. (See Bug#19307)

14.12. The BLACKHOLE Storage Engine

The BLACKHOLE storage engine acts as a “black hole” that accepts data but throws it away and does not store it. Retrievals always return an empty result:

mysql> CREATE TABLE test(i INT, c CHAR(10)) ENGINE = BLACKHOLE;
Query OK, 0 rows affected (0.03 sec)

mysql> INSERT INTO test VALUES(1,'record one'),(2,'record two');
Query OK, 2 rows affected (0.00 sec)
Records: 2  Duplicates: 0  Warnings: 0

mysql> SELECT * FROM test;
Empty set (0.00 sec)

The BLACKHOLE storage engine is included in MySQL-Max binary distributions. To enable this storage engine if you build MySQL from source, invoke configure with the --with-blackhole-storage-engine option.

To examine the source for the BLACKHOLE engine, look in the sql directory of a MySQL source distribution.

When you create a BLACKHOLE table, the server creates a table format file in the database directory. The file begins with the table name and has an .frm extension. There are no other files associated with the table.

The BLACKHOLE storage engine supports all kinds of indexes. That is, you can include index declarations in the table definition.

You can check whether the BLACKHOLE storage engine is available with this statement:

mysql> SHOW VARIABLES LIKE 'have_blackhole_engine';

Inserts into a BLACKHOLE table do not store any data, but if the binary log is enabled, the SQL statements are logged (and replicated to slave servers). This can be useful as a repeater or filter mechanism. For example, suppose that your application requires slave-side filtering rules, but transferring all binary log data to the slave first results in too much traffic. In such a case, it is possible to set up on the master host a “dummy” slave process whose default storage engine is BLACKHOLE, depicted as follows:

Replication using BLACKHOLE
      for filtering

The master writes to its binary log. The “dummymysqld process acts as a slave, applying the desired combination of replicate-do-* and replicate-ignore-* rules, and writes a new, filtered binary log of its own. (See Section 6.9, “Replication Startup Options”.) This filtered log is provided to the slave.

The dummy process does not actually store any data, so there is little processing overhead incurred by running the additional mysqld process on the replication master host. This type of setup can be repeated with additional replication slaves.

Other possible uses for the BLACKHOLE storage engine include:

  • Verification of dump file syntax.

  • Measurement of the overhead from binary logging, by comparing performance using BLACKHOLE with and without binary logging enabled.

  • BLACKHOLE is essentially a “no-op” storage engine, so it could be used for finding performance bottlenecks not related to the storage engine itself.

As of MySQL 5.1.4, the BLACKHOLE engine is transaction-aware, in the sense that committed transactions are written to the binary log and rolled-back transactions are not.